hexsha string | size int64 | ext string | lang string | max_stars_repo_path string | max_stars_repo_name string | max_stars_repo_head_hexsha string | max_stars_repo_licenses list | max_stars_count int64 | max_stars_repo_stars_event_min_datetime string | max_stars_repo_stars_event_max_datetime string | max_issues_repo_path string | max_issues_repo_name string | max_issues_repo_head_hexsha string | max_issues_repo_licenses list | max_issues_count int64 | max_issues_repo_issues_event_min_datetime string | max_issues_repo_issues_event_max_datetime string | max_forks_repo_path string | max_forks_repo_name string | max_forks_repo_head_hexsha string | max_forks_repo_licenses list | max_forks_count int64 | max_forks_repo_forks_event_min_datetime string | max_forks_repo_forks_event_max_datetime string | content string | avg_line_length float64 | max_line_length int64 | alphanum_fraction float64 | qsc_code_num_words_quality_signal int64 | qsc_code_num_chars_quality_signal float64 | qsc_code_mean_word_length_quality_signal float64 | qsc_code_frac_words_unique_quality_signal float64 | qsc_code_frac_chars_top_2grams_quality_signal float64 | qsc_code_frac_chars_top_3grams_quality_signal float64 | qsc_code_frac_chars_top_4grams_quality_signal float64 | qsc_code_frac_chars_dupe_5grams_quality_signal float64 | qsc_code_frac_chars_dupe_6grams_quality_signal float64 | qsc_code_frac_chars_dupe_7grams_quality_signal float64 | qsc_code_frac_chars_dupe_8grams_quality_signal float64 | qsc_code_frac_chars_dupe_9grams_quality_signal float64 | qsc_code_frac_chars_dupe_10grams_quality_signal float64 | qsc_code_frac_chars_replacement_symbols_quality_signal float64 | qsc_code_frac_chars_digital_quality_signal float64 | qsc_code_frac_chars_whitespace_quality_signal float64 | qsc_code_size_file_byte_quality_signal float64 | qsc_code_num_lines_quality_signal float64 | qsc_code_num_chars_line_max_quality_signal float64 | qsc_code_num_chars_line_mean_quality_signal float64 | qsc_code_frac_chars_alphabet_quality_signal float64 | qsc_code_frac_chars_comments_quality_signal float64 | qsc_code_cate_xml_start_quality_signal float64 | qsc_code_frac_lines_dupe_lines_quality_signal float64 | qsc_code_cate_autogen_quality_signal float64 | qsc_code_frac_lines_long_string_quality_signal float64 | qsc_code_frac_chars_string_length_quality_signal float64 | qsc_code_frac_chars_long_word_length_quality_signal float64 | qsc_code_frac_lines_string_concat_quality_signal float64 | qsc_code_cate_encoded_data_quality_signal float64 | qsc_code_frac_chars_hex_words_quality_signal float64 | qsc_code_frac_lines_prompt_comments_quality_signal float64 | qsc_code_frac_lines_assert_quality_signal float64 | qsc_codepython_cate_ast_quality_signal float64 | qsc_codepython_frac_lines_func_ratio_quality_signal float64 | qsc_codepython_cate_var_zero_quality_signal bool | qsc_codepython_frac_lines_pass_quality_signal float64 | qsc_codepython_frac_lines_import_quality_signal float64 | qsc_codepython_frac_lines_simplefunc_quality_signal float64 | qsc_codepython_score_lines_no_logic_quality_signal float64 | qsc_codepython_frac_lines_print_quality_signal float64 | qsc_code_num_words int64 | qsc_code_num_chars int64 | qsc_code_mean_word_length int64 | qsc_code_frac_words_unique null | qsc_code_frac_chars_top_2grams int64 | qsc_code_frac_chars_top_3grams int64 | qsc_code_frac_chars_top_4grams int64 | qsc_code_frac_chars_dupe_5grams int64 | qsc_code_frac_chars_dupe_6grams int64 | qsc_code_frac_chars_dupe_7grams int64 | qsc_code_frac_chars_dupe_8grams int64 | qsc_code_frac_chars_dupe_9grams int64 | qsc_code_frac_chars_dupe_10grams int64 | qsc_code_frac_chars_replacement_symbols int64 | qsc_code_frac_chars_digital int64 | qsc_code_frac_chars_whitespace int64 | qsc_code_size_file_byte int64 | qsc_code_num_lines int64 | qsc_code_num_chars_line_max int64 | qsc_code_num_chars_line_mean int64 | qsc_code_frac_chars_alphabet int64 | qsc_code_frac_chars_comments int64 | qsc_code_cate_xml_start int64 | qsc_code_frac_lines_dupe_lines int64 | qsc_code_cate_autogen int64 | qsc_code_frac_lines_long_string int64 | qsc_code_frac_chars_string_length int64 | qsc_code_frac_chars_long_word_length int64 | qsc_code_frac_lines_string_concat null | qsc_code_cate_encoded_data int64 | qsc_code_frac_chars_hex_words int64 | qsc_code_frac_lines_prompt_comments int64 | qsc_code_frac_lines_assert int64 | qsc_codepython_cate_ast int64 | qsc_codepython_frac_lines_func_ratio int64 | qsc_codepython_cate_var_zero int64 | qsc_codepython_frac_lines_pass int64 | qsc_codepython_frac_lines_import int64 | qsc_codepython_frac_lines_simplefunc int64 | qsc_codepython_score_lines_no_logic int64 | qsc_codepython_frac_lines_print int64 | effective string | hits int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2893e47c6587e2d171c143192e27f6d3602b25a6 | 163 | py | Python | lewas/functools.py | lewas-lab/lewas | a4a05977c26cfebb3a6ee7025a63d2331ac1cac5 | [
"MIT"
] | 1 | 2018-06-21T17:48:37.000Z | 2018-06-21T17:48:37.000Z | lewas/functools.py | lewas-lab/lewas | a4a05977c26cfebb3a6ee7025a63d2331ac1cac5 | [
"MIT"
] | null | null | null | lewas/functools.py | lewas-lab/lewas | a4a05977c26cfebb3a6ee7025a63d2331ac1cac5 | [
"MIT"
] | null | null | null | # see https://mathieularose.com/function-composition-in-python/
def compose(*functions):
return reduce(lambda f, g: lambda x: f(g(x)), functions, lambda x: x)
| 40.75 | 73 | 0.717791 | 25 | 163 | 4.68 | 0.68 | 0.034188 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.122699 | 163 | 3 | 74 | 54.333333 | 0.818182 | 0.374233 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0.5 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
9543295a426ef5c0af79e528fcc4f4c46610e03c | 106 | py | Python | nodebin/blueprints/apiv1/__init__.py | jxltom/nodebin | f7c60cf6ae8ed179340468ad03c65bcd0019daf6 | [
"MIT"
] | null | null | null | nodebin/blueprints/apiv1/__init__.py | jxltom/nodebin | f7c60cf6ae8ed179340468ad03c65bcd0019daf6 | [
"MIT"
] | 1 | 2018-07-17T02:09:28.000Z | 2018-07-17T02:09:28.000Z | nodebin/blueprints/apiv1/__init__.py | jxltom/nodebin | f7c60cf6ae8ed179340468ad03c65bcd0019daf6 | [
"MIT"
] | 1 | 2021-11-10T23:15:08.000Z | 2021-11-10T23:15:08.000Z | from flask import Blueprint
apiv1 = Blueprint('apiv1', __name__)
from . import views
from . import hooks
| 17.666667 | 36 | 0.764151 | 14 | 106 | 5.5 | 0.571429 | 0.363636 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.022472 | 0.160377 | 106 | 5 | 37 | 21.2 | 0.842697 | 0 | 0 | 0 | 0 | 0 | 0.04717 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.75 | 0 | 0.75 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 6 |
954b6388a8f4a8d8111a38ccad9be1869c9ec2cf | 788 | py | Python | iscontained.py | sanjioh/weird_tdd | b13f9c523f0c33e4b289de2114a3616bbea82d28 | [
"MIT"
] | null | null | null | iscontained.py | sanjioh/weird_tdd | b13f9c523f0c33e4b289de2114a3616bbea82d28 | [
"MIT"
] | null | null | null | iscontained.py | sanjioh/weird_tdd | b13f9c523f0c33e4b289de2114a3616bbea82d28 | [
"MIT"
] | null | null | null | # coding: utf-8
def iscontained_step1(contained, container):
return True
iscontained = iscontained_step1
def iscontained_step2(contained, container):
return contained == container
iscontained = iscontained_step2
def iscontained_step3(contained, container):
return contained == []
iscontained = iscontained_step3
def iscontained_step4(contained, container):
return contained == [] or contained == container
iscontained = iscontained_step4
def iscontained_step5(contained, container):
return contained == [] or contained[0] in container
iscontained = iscontained_step5
def iscontained_step6(contained, container):
for item in contained:
if item not in container:
return False
return True
iscontained = iscontained_step6
| 17.511111 | 55 | 0.744924 | 83 | 788 | 6.927711 | 0.277108 | 0.250435 | 0.208696 | 0.229565 | 0.153043 | 0.153043 | 0 | 0 | 0 | 0 | 0 | 0.021875 | 0.187817 | 788 | 44 | 56 | 17.909091 | 0.876563 | 0.016497 | 0 | 0.095238 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0 | 0.238095 | 0.619048 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
9562d27ab3a75ab777840e0b827470323213471f | 104,378 | py | Python | lenv/lib/python3.6/site-packages/Crypto/SelfTest/Hash/test_vectors/keccak/ShortMsgKAT_512.txt.py | shrey-c/DataLeakageDjango | a827c5a09e5501921f9fb97b656755671238dd63 | [
"BSD-3-Clause"
] | 6 | 2020-05-03T12:03:21.000Z | 2020-09-07T08:33:58.000Z | lenv/lib/python3.6/site-packages/Crypto/SelfTest/Hash/test_vectors/keccak/ShortMsgKAT_512.txt.py | shrey-c/DataLeakageDjango | a827c5a09e5501921f9fb97b656755671238dd63 | [
"BSD-3-Clause"
] | 3 | 2020-04-17T06:50:44.000Z | 2022-01-13T02:16:48.000Z | lenv/lib/python3.6/site-packages/Crypto/SelfTest/Hash/test_vectors/keccak/ShortMsgKAT_512.txt.py | shrey-c/DataLeakageDjango | a827c5a09e5501921f9fb97b656755671238dd63 | [
"BSD-3-Clause"
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XXX X XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
XX X XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
| 101.633885 | 516 | 0.975397 | 2,311 | 104,378 | 44.054522 | 0.112505 | 0.020116 | 0.329398 | 0.335625 | 0.356949 | 0.356949 | 0.356949 | 0.356949 | 0.002829 | 0.002829 | 0 | 0 | 0.024603 | 104,378 | 1,026 | 517 | 101.732943 | 1 | 0 | 0 | 0.672302 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 0 | 0 | 1 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
9566a6103bc02fb60c1e4383e36713c8ee0d38aa | 93 | py | Python | module_05/test_hello_word.py | IvanJL/2021_python_selenium | 52ad0afa43664308437658966ec5d989a2db9c02 | [
"Unlicense"
] | null | null | null | module_05/test_hello_word.py | IvanJL/2021_python_selenium | 52ad0afa43664308437658966ec5d989a2db9c02 | [
"Unlicense"
] | null | null | null | module_05/test_hello_word.py | IvanJL/2021_python_selenium | 52ad0afa43664308437658966ec5d989a2db9c02 | [
"Unlicense"
] | null | null | null |
def test_one():
print("First tests case")
def test_two():
print("SECOND TEST CASE") | 15.5 | 29 | 0.645161 | 14 | 93 | 4.142857 | 0.642857 | 0.241379 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.204301 | 93 | 6 | 30 | 15.5 | 0.783784 | 0 | 0 | 0 | 0 | 0 | 0.344086 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0 | 0.5 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
956be9797cc344529b3edc4ff573b43323f1fc56 | 22 | py | Python | soccer_fw/models/neural/__init__.py | szkkteam/soccer_fw | 998ee2dd2f11b86abafd44891f8eb869e038cb47 | [
"MIT"
] | null | null | null | soccer_fw/models/neural/__init__.py | szkkteam/soccer_fw | 998ee2dd2f11b86abafd44891f8eb869e038cb47 | [
"MIT"
] | null | null | null | soccer_fw/models/neural/__init__.py | szkkteam/soccer_fw | 998ee2dd2f11b86abafd44891f8eb869e038cb47 | [
"MIT"
] | null | null | null | from .knn_mlp import * | 22 | 22 | 0.772727 | 4 | 22 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.136364 | 22 | 1 | 22 | 22 | 0.842105 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
95a33c9c31fce2728ba6f71a09cf6e674ab58bb1 | 5,375 | py | Python | synoptico/tests.py | eldarion/synoptico | 742995f68f1ee8cbf58037bcaf91d77283f51833 | [
"MIT"
] | 4 | 2015-04-10T06:34:15.000Z | 2019-12-14T14:40:00.000Z | synoptico/tests.py | eldarion/synoptico | 742995f68f1ee8cbf58037bcaf91d77283f51833 | [
"MIT"
] | null | null | null | synoptico/tests.py | eldarion/synoptico | 742995f68f1ee8cbf58037bcaf91d77283f51833 | [
"MIT"
] | null | null | null | from django.core.exceptions import ValidationError
from django.test import TestCase
from django.contrib.auth.models import User
from .models import Project, Timeline, Event, TimelineMapping
class ValidationTests(TestCase):
def setUp(self):
self.user = User.objects.create_user(username="jtauber")
self.project = Project.objects.create(title="The Hobbit", created_by=self.user)
def test_isbn_validation_error(self):
with self.assertRaises(ValidationError):
Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="notanisbn",
created_by=self.user
)
def test_isbn_validation_error_from_no_right_number_of_digits(self):
with self.assertRaises(ValidationError):
Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="132",
created_by=self.user
)
def test_isbn_validation_valid_with_10_digits(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="0618968633",
created_by=self.user
)
self.assertEquals(timeline.pk, 1)
def test_isbn_validation_valid_with_13_digits(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="9780618968633",
created_by=self.user
)
self.assertEquals(timeline.pk, 1)
def test_page_number_validation_error(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="9780618968633",
created_by=self.user
)
event = Event.objects.create(
project=self.project,
description="Thorin inserts the key",
created_by=self.user
)
with self.assertRaises(ValidationError):
TimelineMapping.objects.create(
timeline=timeline,
event=event,
offset="notapage",
created_by=self.user
)
def test_page_number_validation_works(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_BOOK,
name="The Hobbit (Houghton Mifflin Seventieth Anniversary Edition)",
identifier="9780618968633",
created_by=self.user
)
event = Event.objects.create(
project=self.project,
description="Thorin inserts the key",
created_by=self.user
)
mapping = TimelineMapping.objects.create(
timeline=timeline,
event=event,
offset="194",
created_by=self.user
)
self.assertEquals(mapping.pk, 1)
def test_timecode_validation_error(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_MOVIE,
name="The Hobbit: An Unexpected Journey",
identifier="http://www.imdb.com/title/tt0903624/",
created_by=self.user
)
event = Event.objects.create(
project=self.project,
description="Thorin inserts the key",
created_by=self.user
)
with self.assertRaises(ValidationError):
TimelineMapping.objects.create(
timeline=timeline,
event=event,
offset="notatimecode",
created_by=self.user
)
def test_timecode_validation_works(self):
timeline = Timeline.objects.create(
project=self.project,
media_type=Timeline.MEDIA_TYPE_MOVIE,
name="The Hobbit: An Unexpected Journey",
identifier="http://www.imdb.com/title/tt0903624/",
created_by=self.user
)
event = Event.objects.create(
project=self.project,
description="Thorin inserts the key",
created_by=self.user
)
mapping = TimelineMapping.objects.create(
timeline=timeline,
event=event,
offset="00:30:15",
created_by=self.user
)
self.assertEquals(mapping.pk, 1)
class OrderingTests(TestCase):
fixtures = ["projects", "hobbit_timelines", "hobbit_mappings"]
def setUp(self):
self.user = User.objects.create_user(username="jtauber")
def test_page_ordering(self):
pages = [
x.offset.strip()
for x in Timeline.objects.get(pk=1).events()
]
self.assertEquals(pages, ["9", "40", "70", "102", "110", "137", "159", "194", "208", "248"])
| 35.130719 | 100 | 0.601302 | 540 | 5,375 | 5.827778 | 0.196296 | 0.0483 | 0.070226 | 0.091833 | 0.832221 | 0.825866 | 0.800445 | 0.800445 | 0.78837 | 0.733715 | 0 | 0.02957 | 0.307907 | 5,375 | 152 | 101 | 35.361842 | 0.816398 | 0 | 0 | 0.664179 | 0 | 0 | 0.142698 | 0 | 0 | 0 | 0 | 0 | 0.067164 | 1 | 0.08209 | false | 0 | 0.029851 | 0 | 0.134328 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
95a43631042c6880007b556158ce8f7fcf840333 | 34 | py | Python | chatty_goose/pipeline/__init__.py | saileshnankani/chatty-goose | ef3a27119d6825a96ae85d1453d6b4eac4ed22b7 | [
"Apache-2.0"
] | 24 | 2021-03-08T09:53:59.000Z | 2022-03-17T06:47:06.000Z | chatty_goose/pipeline/__init__.py | saileshnankani/chatty-goose | ef3a27119d6825a96ae85d1453d6b4eac4ed22b7 | [
"Apache-2.0"
] | 10 | 2021-03-08T13:35:54.000Z | 2021-11-15T03:32:37.000Z | chatty_goose/pipeline/__init__.py | saileshnankani/chatty-goose | ef3a27119d6825a96ae85d1453d6b4eac4ed22b7 | [
"Apache-2.0"
] | 8 | 2021-03-03T00:37:18.000Z | 2021-08-01T00:50:47.000Z | from .retrieval_pipeline import *
| 17 | 33 | 0.823529 | 4 | 34 | 6.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 34 | 1 | 34 | 34 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
2545250593202a8ccc16041da6b6f8ad2bcc4ca3 | 37 | py | Python | test/tests/relative_import2.py | aisk/pyston | ac69cfef0621dbc8901175e84fa2b5cb5781a646 | [
"BSD-2-Clause",
"Apache-2.0"
] | 1 | 2020-02-06T14:28:45.000Z | 2020-02-06T14:28:45.000Z | test/tests/relative_import2.py | aisk/pyston | ac69cfef0621dbc8901175e84fa2b5cb5781a646 | [
"BSD-2-Clause",
"Apache-2.0"
] | null | null | null | test/tests/relative_import2.py | aisk/pyston | ac69cfef0621dbc8901175e84fa2b5cb5781a646 | [
"BSD-2-Clause",
"Apache-2.0"
] | 1 | 2020-02-06T14:29:00.000Z | 2020-02-06T14:29:00.000Z | from relative_import2_pkg import foo
| 18.5 | 36 | 0.891892 | 6 | 37 | 5.166667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.030303 | 0.108108 | 37 | 1 | 37 | 37 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c27eaded503007c2b19dc56aa83318427399b41a | 21 | py | Python | pkg/strategy/__init__.py | skanehira1126/darts_app | f2dff7602d22abe64fc6655ff932ab8e6dea5e5e | [
"MIT"
] | 1 | 2020-04-28T12:05:22.000Z | 2020-04-28T12:05:22.000Z | pkg/strategy/__init__.py | skanehira1126/darts_app | f2dff7602d22abe64fc6655ff932ab8e6dea5e5e | [
"MIT"
] | null | null | null | pkg/strategy/__init__.py | skanehira1126/darts_app | f2dff7602d22abe64fc6655ff932ab8e6dea5e5e | [
"MIT"
] | null | null | null | from . import zeroone | 21 | 21 | 0.809524 | 3 | 21 | 5.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 21 | 1 | 21 | 21 | 0.944444 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
6c569e425a4f24d2489efc5745bf27166c3ef479 | 85 | py | Python | reqlog/pages/reports/__init__.py | JFF-Bohdan/reqlog | a7ba7b6e12609d736b3cd8cd8bc2913d511848ee | [
"MIT"
] | null | null | null | reqlog/pages/reports/__init__.py | JFF-Bohdan/reqlog | a7ba7b6e12609d736b3cd8cd8bc2913d511848ee | [
"MIT"
] | null | null | null | reqlog/pages/reports/__init__.py | JFF-Bohdan/reqlog | a7ba7b6e12609d736b3cd8cd8bc2913d511848ee | [
"MIT"
] | null | null | null | from .page_all_requests import * # noqa
from .page_request_details import * # noqa | 42.5 | 43 | 0.764706 | 12 | 85 | 5.083333 | 0.666667 | 0.262295 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.164706 | 85 | 2 | 43 | 42.5 | 0.859155 | 0.105882 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
6c847bc1d60e1302ce073f86ff4b3dd35ee39bb7 | 7,841 | py | Python | sdi_utils.py | erelsibm/sdi | 4094079579a8fe52cd628bb755226aa8c3215e2e | [
"Apache-2.0"
] | null | null | null | sdi_utils.py | erelsibm/sdi | 4094079579a8fe52cd628bb755226aa8c3215e2e | [
"Apache-2.0"
] | null | null | null | sdi_utils.py | erelsibm/sdi | 4094079579a8fe52cd628bb755226aa8c3215e2e | [
"Apache-2.0"
] | null | null | null | from tempfile import NamedTemporaryFile
import requests
import json
import pickle
import numpy as np
from io import StringIO
import os
def serializeObject(pythonObj):
return pickle.dumps(pythonObj, pickle.HIGHEST_PROTOCOL)
def deserializeObject(pickledObj):
return pickle.loads(pickledObj)
def serializeKerasModel(model):
with NamedTemporaryFile() as f:
model.save(f.name)
f.seek(0)
obj = f.read()
return obj
def deserializeKerasModel(obj):
from keras.models import Model,load_model
with NamedTemporaryFile(mode='wb') as f:
f.write(obj)
f.flush()
model = load_model(f.name)
return model
def serializeNumpyArray(arr):
with NamedTemporaryFile() as f:
np.save(f, arr)
f.seek(0)
obj = f.read()
f.close()
return obj
def serializeFile(path):
with open(path, mode='rb') as f:
obj = f.read()
return obj
def put_to_objectstore(credentials, object_name, my_data, binary=True, region='dallas'):
print('my_data', len(my_data))
url1 = ''.join(['https://identity.open.softlayer.com', '/v3/auth/tokens'])
data = {'auth': {'identity': {'methods': ['password'],
'password': {'user': {'name': credentials['username'],'domain': {'id': credentials['domain_id']},
'password': credentials['password']}}}}}
headers1 = {'Content-Type': 'application/json'}
resp1 = requests.post(url=url1, data=json.dumps(data), headers=headers1)
resp1_body = resp1.json()
for e1 in resp1_body['token']['catalog']:
if(e1['type']=='object-store'):
for e2 in e1['endpoints']:
if(e2['interface']=='public'and e2['region']==region):
url2 = ''.join([e2['url'],'/', credentials['container'], '/', object_name])
s_subject_token = resp1.headers['x-subject-token']
headers_accept = 'application/octet-stream' if (binary) else 'application/json'
headers2 = {'X-Auth-Token': s_subject_token, 'accept': headers_accept}
resp2 = requests.put(url=url2, headers=headers2, data = my_data )
def get_from_objectstore(credentials, object_name, binary=True, region='dallas'):
url1 = ''.join(['https://identity.open.softlayer.com', '/v3/auth/tokens'])
data = {'auth': {'identity': {'methods': ['password'], 'password': {'user': {'name': credentials['username'],'domain': {'id': credentials['domain_id']}, 'password': credentials['password']}}}}}
headers1 = {'Content-Type': 'application/json'}
resp1 = requests.post(url=url1, data=json.dumps(data), headers=headers1)
resp1_body = resp1.json()
for e1 in resp1_body['token']['catalog']:
if(e1['type']=='object-store'):
for e2 in e1['endpoints']:
if(e2['interface']=='public'and e2['region']==region):
url2 = ''.join([e2['url'],'/', credentials['container'], '/', object_name])
s_subject_token = resp1.headers['x-subject-token']
headers_accept = 'application/octet-stream' if (binary) else 'application/json'
headers2 = {'X-Auth-Token': s_subject_token, 'accept': headers_accept}
resp2 = requests.get(url=url2, headers=headers2)
res = resp2.content if (binary) else StringIO(resp2.text)
return res
def put_to_cloud_object_storage(api_key, full_object_path, my_data, auth_endpoint="https://iam.ng.bluemix.net/oidc/token", service_endpoint="https://s3-api.us-geo.objectstorage.softlayer.net"):
print('my_data', len(my_data))
response=requests.post(
url=auth_endpoint,
headers={"Content-Type": "application/x-www-form-urlencoded"},
params={"grant_type":"urn:ibm:params:oauth:grant-type:apikey","apikey":api_key},
verify=True)
access_token=response.json()["access_token"]
response=requests.put(
url=service_endpoint+"/"+full_object_path,
headers={"Authorization": "bearer " + access_token},
data = my_data)
return response
def get_from_cloud_object_storage(api_key, full_object_path, auth_endpoint="https://iam.ng.bluemix.net/oidc/token", service_endpoint="https://s3-api.us-geo.objectstorage.softlayer.net"):
response=requests.post(
url=auth_endpoint,
headers={"Content-Type": "application/x-www-form-urlencoded"},
params={"grant_type":"urn:ibm:params:oauth:grant-type:apikey","apikey":api_key},
verify=True)
access_token=response.json()["access_token"]
response=requests.get(
url=service_endpoint+"/"+full_object_path,
headers={"Authorization": "bearer " + access_token},
params=None,
verify=True)
return response.content
# Make sure to install: ibm-cos-sdk
# !pip install ibm-cos-sdk
# https://github.com/IBM/ibm-cos-sdk-python
def create_messagehub_producer(username, password, kafka_brokers_sasl = [], sasl_mechanism = 'PLAIN', security_protocol = 'SASL_SSL', value_serializer=lambda v: json.dumps(v).encode('utf-8')):
import ssl
from kafka import KafkaProducer
from kafka.errors import KafkaError
if (kafka_brokers_sasl == []):
kafka_brokers_sasl = [
"kafka01-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka02-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka03-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka04-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka05-prod01.messagehub.services.us-south.bluemix.net:9093"
]
# Create a new context using system defaults, disable all but TLS1.2
context = ssl.create_default_context()
context.options &= ssl.OP_NO_TLSv1
context.options &= ssl.OP_NO_TLSv1_1
producer = KafkaProducer(bootstrap_servers = kafka_brokers_sasl,
sasl_plain_username = username,
sasl_plain_password = password,
security_protocol = security_protocol,
ssl_context = context,
sasl_mechanism = sasl_mechanism,
value_serializer=value_serializer)
return producer
def create_messagehub_consumer(username, password, kafka_brokers_sasl = [], sasl_mechanism = 'PLAIN', security_protocol = 'SASL_SSL', value_deserializer=lambda v: json.loads(v).encode('utf-8')):
import ssl
from kafka import KafkaConsumer
from kafka.errors import KafkaError
if (kafka_brokers_sasl == []):
kafka_brokers_sasl = [
"kafka01-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka02-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka03-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka04-prod01.messagehub.services.us-south.bluemix.net:9093",
"kafka05-prod01.messagehub.services.us-south.bluemix.net:9093"
]
# Create a new context using system defaults, disable all but TLS1.2
context = ssl.create_default_context()
context.options &= ssl.OP_NO_TLSv1
context.options &= ssl.OP_NO_TLSv1_1
consumer = KafkaConsumer(bootstrap_servers = kafka_brokers_sasl,
sasl_plain_username = username,
sasl_plain_password = password,
security_protocol = security_protocol,
ssl_context = context,
sasl_mechanism = sasl_mechanism,
value_deserializer=value_deserializer)
return consumer
| 44.551136 | 197 | 0.627981 | 896 | 7,841 | 5.340402 | 0.22433 | 0.025078 | 0.050157 | 0.054336 | 0.741902 | 0.741902 | 0.721003 | 0.721003 | 0.70512 | 0.690491 | 0 | 0.023874 | 0.241423 | 7,841 | 175 | 198 | 44.805714 | 0.780599 | 0.029843 | 0 | 0.612676 | 0 | 0 | 0.22576 | 0.103934 | 0 | 0 | 0 | 0 | 0 | 1 | 0.084507 | false | 0.056338 | 0.098592 | 0.014085 | 0.260563 | 0.014085 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 6 |
665ef14072dc226c1b2fb681107ea12798e5429e | 30 | py | Python | mlflow/Exceptions/__init__.py | BBBBlarry/mlflow | e8f5b9450ba6d3b68fe0cbb530840c0a760d3b08 | [
"MIT"
] | null | null | null | mlflow/Exceptions/__init__.py | BBBBlarry/mlflow | e8f5b9450ba6d3b68fe0cbb530840c0a760d3b08 | [
"MIT"
] | null | null | null | mlflow/Exceptions/__init__.py | BBBBlarry/mlflow | e8f5b9450ba6d3b68fe0cbb530840c0a760d3b08 | [
"MIT"
] | null | null | null | from graph_exceptions import * | 30 | 30 | 0.866667 | 4 | 30 | 6.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 30 | 1 | 30 | 30 | 0.925926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
66a51f9efc90e29446e895123afb9bb0b0e968f6 | 33 | py | Python | antalla/__init__.py | sambacha/antalla | 241f49058e4295aa9f5bc62efe517388d9256520 | [
"MIT"
] | 9 | 2019-12-12T13:57:31.000Z | 2021-08-13T15:51:13.000Z | antalla/__init__.py | sambacha/antalla | 241f49058e4295aa9f5bc62efe517388d9256520 | [
"MIT"
] | 5 | 2021-09-17T09:14:55.000Z | 2022-02-26T21:06:07.000Z | antalla/__init__.py | sambacha/antalla | 241f49058e4295aa9f5bc62efe517388d9256520 | [
"MIT"
] | 3 | 2020-04-27T03:30:58.000Z | 2020-09-07T00:08:59.000Z | from . import exchange_listeners
| 16.5 | 32 | 0.848485 | 4 | 33 | 6.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121212 | 33 | 1 | 33 | 33 | 0.931034 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
66dd4eef9456a62cc010cac25bc6b4176a9b5194 | 4,290 | py | Python | hangman.py | AlikanakelaKarwowski/hangman | eead293ba078b155dbc760a2b36e179dc80f3a44 | [
"MIT"
] | 1 | 2020-09-21T15:50:53.000Z | 2020-09-21T15:50:53.000Z | hangman.py | AlikanakelaKarwowski/hangman | eead293ba078b155dbc760a2b36e179dc80f3a44 | [
"MIT"
] | null | null | null | hangman.py | AlikanakelaKarwowski/hangman | eead293ba078b155dbc760a2b36e179dc80f3a44 | [
"MIT"
] | null | null | null | from os import system, name
def hang(number):
switcher = {
0: hangman,
1: hangman_head,
2: hangman_body,
3: hangman_arm1,
4: hangman_arm2,
5: hangman_leg1,
6: hangman_leg2,
7: game_over
}
switch = switcher.get(number)
return switch()
def game_over():
print("Game Over")
def hangman():
print(" __________",
"\n | |",
"\n | |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_head():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_body():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n | |",
"\n | |",
"\n | |",
"\n | |",
"\n |",
"\n |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_arm1():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n | |",
"\n ---| |",
"\n | |",
"\n | |",
"\n |",
"\n |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_arm2():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n | |",
"\n ---|--- |",
"\n | |",
"\n | |",
"\n |",
"\n |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_leg1():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n | |",
"\n ---|--- |",
"\n | |",
"\n | |",
"\n / |",
"\n / |",
"\n |",
"\n _____________|_____",
"\n ")
def hangman_leg2():
print(" __________",
"\n | |",
"\n | |",
"\n _/_\_ |",
"\n |_| |",
"\n | |",
"\n ---|--- |",
"\n | |",
"\n | |",
"\n / \ |",
"\n / \ |",
"\n |",
"\n _____________|_____",
"\n ")
# define our clear function
def clear_screen():
if name == 'nt':
_ = system('cls')
# for mac and linux(here, os.name is 'posix')
else:
_ = system('clear')
| 28.791946 | 49 | 0.174126 | 186 | 4,290 | 2.741935 | 0.252688 | 0.329412 | 0.452941 | 0.54902 | 0.364706 | 0.364706 | 0.364706 | 0.364706 | 0.364706 | 0.364706 | 0 | 0.011503 | 0.675758 | 4,290 | 148 | 50 | 28.986486 | 0.35514 | 0.016084 | 0 | 0.769841 | 0 | 0 | 0.532243 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.079365 | false | 0 | 0.007937 | 0 | 0.095238 | 0.063492 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
dd067152854705afb710e739aaabbb5527dee4d9 | 211 | py | Python | main/SteppableDemos/FastDiffusionSolver2DFE/diffusion_fast_box/Simulation/diffusion_fast_box.py | JulianoGianlupi/nh-cc3d-4x-base-tool | c0f4aceebd4c5bf3ec39e831ef851e419b161259 | [
"CC0-1.0"
] | null | null | null | main/SteppableDemos/FastDiffusionSolver2DFE/diffusion_fast_box/Simulation/diffusion_fast_box.py | JulianoGianlupi/nh-cc3d-4x-base-tool | c0f4aceebd4c5bf3ec39e831ef851e419b161259 | [
"CC0-1.0"
] | null | null | null | main/SteppableDemos/FastDiffusionSolver2DFE/diffusion_fast_box/Simulation/diffusion_fast_box.py | JulianoGianlupi/nh-cc3d-4x-base-tool | c0f4aceebd4c5bf3ec39e831ef851e419b161259 | [
"CC0-1.0"
] | 1 | 2021-02-26T21:50:29.000Z | 2021-02-26T21:50:29.000Z | from cc3d import CompuCellSetup
from diffusion_fast_boxSteppables import diffusion_fast_boxSteppable
CompuCellSetup.register_steppable(steppable=diffusion_fast_boxSteppable(frequency=1))
CompuCellSetup.run()
| 26.375 | 85 | 0.890995 | 23 | 211 | 7.869565 | 0.565217 | 0.21547 | 0.276243 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010101 | 0.061611 | 211 | 7 | 86 | 30.142857 | 0.90404 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
06b96446df50b23fa4f6e27677197381f8c48371 | 48 | py | Python | scripts/portal/106030600_east00.py | G00dBye/YYMS | 1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb | [
"MIT"
] | 54 | 2019-04-16T23:24:48.000Z | 2021-12-18T11:41:50.000Z | scripts/portal/106030600_east00.py | G00dBye/YYMS | 1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb | [
"MIT"
] | 3 | 2019-05-19T15:19:41.000Z | 2020-04-27T16:29:16.000Z | scripts/portal/106030600_east00.py | G00dBye/YYMS | 1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb | [
"MIT"
] | 49 | 2020-11-25T23:29:16.000Z | 2022-03-26T16:20:24.000Z | # 106030600
sm.warp(106030600, 3)
sm.dispose()
| 9.6 | 21 | 0.708333 | 7 | 48 | 4.857143 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.452381 | 0.125 | 48 | 4 | 22 | 12 | 0.357143 | 0.1875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
6623edac80b69145636dd53b86a1281328513720 | 18,721 | py | Python | src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/Languages/bg.py | neurodebian/htcondor | 113a5c9921a4fce8a21e3ab96b2c1ba47441bf39 | [
"Apache-2.0"
] | 217 | 2015-01-08T04:49:42.000Z | 2022-03-27T10:11:58.000Z | src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/Languages/bg.py | neurodebian/htcondor | 113a5c9921a4fce8a21e3ab96b2c1ba47441bf39 | [
"Apache-2.0"
] | 185 | 2015-05-03T13:26:31.000Z | 2022-03-28T03:08:59.000Z | src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/Languages/bg.py | neurodebian/htcondor | 113a5c9921a4fce8a21e3ab96b2c1ba47441bf39 | [
"Apache-2.0"
] | 133 | 2015-02-11T09:17:45.000Z | 2022-03-31T07:28:54.000Z | apiAttachAvailable = u'\u0414\u043e\u0441\u0442\u044a\u043f\u0435\u043d \u0447\u0440\u0435\u0437 API'
apiAttachNotAvailable = u'\u041d\u0435\u0434\u043e\u0441\u0442\u044a\u043f\u0435\u043d'
apiAttachPendingAuthorization = u'\u0427\u0430\u043a\u0430 \u0441\u0435 \u043e\u0442\u043e\u0440\u0438\u0437\u0430\u0446\u0438\u044f'
apiAttachRefused = u'\u041e\u0442\u043a\u0430\u0437\u0430\u043d\u0430'
apiAttachSuccess = u'\u0423\u0441\u043f\u0435\u0445'
apiAttachUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
budDeletedFriend = u'\u0418\u0437\u0442\u0440\u0438\u0442 \u043e\u0442 \u0421\u043f\u0438\u0441\u044a\u043a\u0430 \u0441 \u043f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
budFriend = u'\u041f\u0440\u0438\u044f\u0442\u0435\u043b'
budNeverBeenFriend = u'\u041d\u0438\u043a\u043e\u0433\u0430 \u043d\u0435 \u0435 \u0431\u0438\u043b \u0432 \u0421\u043f\u0438\u0441\u044a\u043a\u0430 \u0441 \u043f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
budPendingAuthorization = u'\u0427\u0430\u043a\u0430 \u0441\u0435 \u043e\u0442\u043e\u0440\u0438\u0437\u0430\u0446\u0438\u044f'
budUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cfrBlockedByRecipient = u'\u041e\u0431\u0430\u0436\u0434\u0430\u043d\u0435\u0442\u043e \u0435 \u0431\u043b\u043e\u043a\u0438\u0440\u0430\u043d\u043e \u043e\u0442 \u043f\u0440\u0438\u0435\u043c\u0430\u0449\u0438\u044f'
cfrMiscError = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430 \u0433\u0440\u0435\u0448\u043a\u0430'
cfrNoCommonCodec = u'\u041d\u044f\u043c\u0430 \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449 \u043a\u043e\u0434\u0435\u043a'
cfrNoProxyFound = u'\u041d\u044f\u043c\u0430 \u043d\u0430\u043c\u0435\u0440\u0435\u043d\u0438 \u043f\u0440\u043e\u043a\u0441\u0438 \u0441\u044a\u0440\u0432\u044a\u0440\u0438'
cfrNotAuthorizedByRecipient = u'\u0422\u043e\u0437\u0438 \u043f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b \u043d\u0435 \u0435 \u043e\u0442\u043e\u0440\u0438\u0437\u0438\u0440\u0430\u043d \u043e\u0442 \u043f\u0440\u0438\u0435\u043c\u0430\u0449\u0438\u044f'
cfrRecipientNotFriend = u'\u041f\u0440\u0438\u0435\u043c\u0430\u0449\u0438\u044f\u0442 \u043d\u0435 \u0435 \u043f\u0440\u0438\u044f\u0442\u0435\u043b'
cfrRemoteDeviceError = u'\u041f\u0440\u043e\u0431\u043b\u0435\u043c \u0441 \u043e\u0442\u0434\u0430\u043b\u0435\u0447\u0435\u043d\u043e \u0437\u0432\u0443\u043a\u043e\u0432\u043e \u0443\u0441\u0442\u0440\u043e\u0439\u0441\u0442\u0432\u043e'
cfrSessionTerminated = u'\u041f\u0440\u0435\u043a\u0440\u0430\u0442\u0435\u043d\u0430 \u0441\u0435\u0441\u0438\u044f'
cfrSoundIOError = u'\u0412\u0445\u043e\u0434\u043d\u043e/\u0438\u0437\u0445\u043e\u0434\u043d\u0430 \u0433\u0440\u0435\u0448\u043a\u0430 \u0441\u044a\u0441 \u0437\u0432\u0443\u043a\u0430'
cfrSoundRecordingError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u0437\u0430\u043f\u0438\u0441\u0430 \u043d\u0430 \u0437\u0432\u0443\u043a'
cfrUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cfrUserDoesNotExist = u'\u0410\u0431\u043e\u043d\u0430\u0442\u044a\u0442/\u0442\u0435\u043b\u0435\u0444\u043e\u043d\u043d\u0438\u044f\u0442 \u043d\u043e\u043c\u0435\u0440 \u043d\u0435 \u0441\u044a\u0449\u0435\u0441\u0442\u0432\u0443\u0432\u0430'
cfrUserIsOffline = u'\u0422\u043e\u0439/\u0442\u044f \u0435 \u0438\u0437\u0432\u044a\u043d \u043b\u0438\u043d\u0438\u044f.'
chsAllCalls = u'\u0421\u0442\u0430\u0440 \u0434\u0438\u0430\u043b\u043e\u0433'
chsDialog = u'\u0414\u0438\u0430\u043b\u043e\u0433'
chsIncomingCalls = u'\u041c\u043d\u043e\u0437\u0438\u043d\u0430 \u0442\u0440\u044f\u0431\u0432\u0430 \u0434\u0430 \u043f\u0440\u0438\u0435\u043c\u0430\u0442'
chsLegacyDialog = u'\u0421\u0442\u0430\u0440 \u0434\u0438\u0430\u043b\u043e\u0433'
chsMissedCalls = u'\u0414\u0438\u0430\u043b\u043e\u0433'
chsMultiNeedAccept = u'\u041c\u043d\u043e\u0437\u0438\u043d\u0430 \u0442\u0440\u044f\u0431\u0432\u0430 \u0434\u0430 \u043f\u0440\u0438\u0435\u043c\u0430\u0442'
chsMultiSubscribed = u'\u041c\u043d\u043e\u0437\u0438\u043d\u0430 \u0441\u0430 \u0430\u0431\u043e\u043d\u0430\u0442\u0438'
chsOutgoingCalls = u'\u041c\u043d\u043e\u0437\u0438\u043d\u0430 \u0441\u0430 \u0430\u0431\u043e\u043d\u0430\u0442\u0438'
chsUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
chsUnsubscribed = u'\u041d\u0435 \u0435 \u0430\u0431\u043e\u043d\u0430\u0442'
clsBusy = u'\u0417\u0430\u0435\u0442\u043e'
clsCancelled = u'\u041f\u0440\u0435\u043a\u0440\u0430\u0442\u0435\u043d'
clsEarlyMedia = u'\u0412\u044a\u0437\u043f\u0440\u043e\u0438\u0437\u0432\u0435\u0436\u0434\u0430\u043d\u0435 \u043d\u0430 \u043f\u0440\u0435\u0434\u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u0435\u043d \u0448\u0443\u043c (Early Media)'
clsFailed = u'\u0417\u0430 \u0441\u044a\u0436\u0430\u043b\u0435\u043d\u0438\u0435, \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u044a\u0442 \u0441\u0435 \u0440\u0430\u0437\u043f\u0430\u0434\u043d\u0430!'
clsFinished = u'\u041f\u0440\u0438\u043a\u043b\u044e\u0447\u0435\u043d'
clsInProgress = u'\u0412 \u043f\u0440\u043e\u0446\u0435\u0441 \u043d\u0430 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440'
clsLocalHold = u'\u041d\u0430 \u0438\u0437\u0447\u0430\u043a\u0432\u0430\u043d\u0435 \u043e\u0442 \u0432\u0430\u0448\u0430 \u0441\u0442\u0440\u0430\u043d\u0430'
clsMissed = u'\u043f\u0440\u043e\u043f\u0443\u0441\u043d\u0430\u0442 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440'
clsOnHold = u'\u0417\u0430\u0434\u044a\u0440\u0436\u0430\u043d\u0435'
clsRefused = u'\u041e\u0442\u043a\u0430\u0437\u0430\u043d\u0430'
clsRemoteHold = u'\u041d\u0430 \u0438\u0437\u0447\u0430\u043a\u0432\u0430\u043d\u0435 \u043e\u0442 \u043e\u0442\u0441\u0440\u0435\u0449\u043d\u0430\u0442\u0430 \u0441\u0442\u0440\u0430\u043d\u0430'
clsRinging = u'\u0433\u043e\u0432\u043e\u0440\u0438\u0442\u0435'
clsRouting = u'\u041f\u0440\u0435\u043d\u0430\u0441\u043e\u0447\u0432\u0430\u043d\u0435'
clsTransferred = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
clsTransferring = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
clsUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
clsUnplaced = u'\u041d\u0438\u043a\u043e\u0433\u0430 \u043d\u0435 \u0435 \u043f\u0440\u043e\u0432\u0435\u0436\u0434\u0430\u043d'
clsVoicemailBufferingGreeting = u'\u0411\u0443\u0444\u0435\u0440\u0438\u0440\u0430\u043d\u0435 \u043d\u0430 \u043f\u043e\u0437\u0434\u0440\u0430\u0432\u0430'
clsVoicemailCancelled = u'\u0413\u043b\u0430\u0441\u043e\u0432\u0430\u0442\u0430 \u043f\u043e\u0449\u0430 \u043e\u0442\u043c\u0435\u043d\u0435\u043d\u0430'
clsVoicemailFailed = u'\u041f\u0440\u043e\u0432\u0430\u043b\u0435\u043d\u043e \u0433\u043b\u0430\u0441\u043e\u0432\u043e \u0441\u044a\u043e\u0431\u0449\u0435\u043d\u0438\u0435'
clsVoicemailPlayingGreeting = u'\u0412\u044a\u0437\u043f\u0440\u043e\u0438\u0437\u0432\u0435\u0436\u0434\u0430\u043d\u0435 \u043d\u0430 \u043f\u043e\u0437\u0434\u0440\u0430\u0432\u0430'
clsVoicemailRecording = u'\u0417\u0430\u043f\u0438\u0441 \u043d\u0430 \u0433\u043b\u0430\u0441\u043e\u0432\u043e \u0441\u044a\u043e\u0431\u0449\u0435\u043d\u0438\u0435'
clsVoicemailSent = u'\u0413\u043b\u0430\u0441\u043e\u0432\u0430\u0442\u0430 \u043f\u043e\u0449\u0430 \u0438\u0437\u043f\u0440\u0430\u0442\u0435\u043d\u0430'
clsVoicemailUploading = u'\u0413\u043b\u0430\u0441\u043e\u0432\u0430\u0442\u0430 \u043f\u043e\u0449\u0430 \u0441\u0435 \u043a\u0430\u0447\u0432\u0430'
cltIncomingP2P = u'\u0412\u0445\u043e\u0434\u044f\u0449\u043e Peer-to-Peer \u043e\u0431\u0430\u0436\u0434\u0430\u043d\u0435'
cltIncomingPSTN = u'\u0412\u0445\u043e\u0434\u044f\u0449\u043e \u0442\u0435\u043b\u0435\u0444\u043e\u043d\u043d\u043e \u043e\u0431\u0430\u0436\u0434\u0430\u043d\u0435'
cltOutgoingP2P = u'\u0418\u0437\u0445\u043e\u0434\u044f\u0449\u043e Peer-to-Peer \u043e\u0431\u0430\u0436\u0434\u0430\u043d\u0435'
cltOutgoingPSTN = u'\u0418\u0437\u0445\u043e\u0434\u044f\u0449\u043e \u0442\u0435\u043b\u0435\u0444\u043e\u043d\u043d\u043e \u043e\u0431\u0430\u0436\u0434\u0430\u043d\u0435'
cltUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cmeAddedMembers = u'\u0414\u043e\u0431\u0430\u0432\u0438 \u0447\u043b\u0435\u043d\u043e\u0432\u0435'
cmeCreatedChatWith = u'\u0421\u044a\u0437\u0434\u0430\u0434\u0435 \u0447\u0430\u0442 \u0441\u044a\u0441'
cmeEmoted = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cmeLeft = u'\u041d\u0430\u043f\u0443\u0441\u043d\u0430'
cmeSaid = u'\u041a\u0430\u0437\u0430'
cmeSawMembers = u'\u0412\u0438\u0434\u044f \u0447\u043b\u0435\u043d\u043e\u0432\u0435'
cmeSetTopic = u'\u0417\u0430\u0434\u0430\u0439 \u0442\u0435\u043c\u0430'
cmeUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cmsRead = u'\u041f\u0440\u043e\u0447\u0435\u0442\u0435\u043d\u043e'
cmsReceived = u'\u041f\u043e\u043b\u0443\u0447\u0435\u043d\u043e'
cmsSending = u'\u0418\u0437\u043f\u0440\u0430\u0449\u0430\u043d\u0435...'
cmsSent = u'\u041f\u0440\u0430\u0442\u0435\u043d\u0430'
cmsUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
conConnecting = u'\u0412 \u043f\u0440\u043e\u0446\u0435\u0441 \u043d\u0430 \u0441\u0432\u044a\u0440\u0437\u0432\u0430\u043d\u0435'
conOffline = u'\u0418\u0437\u0432\u044a\u043d \u043b\u0438\u043d\u0438\u044f'
conOnline = u'\u041d\u0430 \u043b\u0438\u043d\u0438\u044f'
conPausing = u'\u041f\u0430\u0443\u0437\u0430'
conUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cusAway = u'\u041e\u0442\u0441\u044a\u0441\u0442\u0432\u0430\u0449'
cusDoNotDisturb = u'\u041e\u0442\u043f\u043e\u0447\u0438\u0432\u0430\u0449'
cusInvisible = u'\u0418\u043d\u043a\u043e\u0433\u043d\u0438\u0442\u043e'
cusLoggedOut = u'\u0418\u0437\u0432\u044a\u043d \u043b\u0438\u043d\u0438\u044f'
cusNotAvailable = u'\u041d\u0435\u0434\u043e\u0441\u0442\u044a\u043f\u0435\u043d'
cusOffline = u'\u0418\u0437\u0432\u044a\u043d \u043b\u0438\u043d\u0438\u044f'
cusOnline = u'\u041d\u0430 \u043b\u0438\u043d\u0438\u044f'
cusSkypeMe = u'\u0421\u043a\u0430\u0439\u043f\u0432\u0430\u0449'
cusUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
cvsBothEnabled = u'\u0418\u0437\u043f\u0440\u0430\u0449\u0430\u043d\u0435 \u0438 \u043f\u043e\u043b\u0443\u0447\u0430\u0432\u0430\u043d\u0435 \u043d\u0430 \u0432\u0438\u0434\u0435\u043e'
cvsNone = u'\u041d\u044f\u043c\u0430 \u0432\u0438\u0434\u0435\u043e'
cvsReceiveEnabled = u'\u041f\u043e\u043b\u0443\u0447\u0430\u0432\u0430\u043d\u0435 \u043d\u0430 \u0432\u0438\u0434\u0435\u043e'
cvsSendEnabled = u'\u0418\u0437\u043f\u0440\u0430\u0449\u0430\u043d\u0435 \u043d\u0430 \u0432\u0438\u0434\u0435\u043e'
cvsUnknown = u''
grpAllFriends = u'\u0412\u0441\u0438\u0447\u043a\u0438 \u041f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
grpAllUsers = u'\u0412\u0441\u0438\u0447\u043a\u0438 \u0430\u0431\u043e\u043d\u0430\u0442\u0438'
grpCustomGroup = u'\u041f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b\u0441\u043a\u0430'
grpOnlineFriends = u'\u041f\u0440\u0438\u044f\u0442\u0435\u043b\u0438 \u043e\u043d\u043b\u0430\u0439\u043d'
grpPendingAuthorizationFriends = u'\u0427\u0430\u043a\u0430 \u0441\u0435 \u043e\u0442\u043e\u0440\u0438\u0437\u0430\u0446\u0438\u044f'
grpProposedSharedGroup = u'Proposed Shared Group'
grpRecentlyContactedUsers = u'\u0410\u0431\u043e\u043d\u0430\u0442\u0438, \u0441 \u043a\u043e\u0438\u0442\u043e \u0441\u043a\u043e\u0440\u043e \u0435 \u0443\u0441\u0442\u0430\u043d\u043e\u0432\u0435\u043d\u0430 \u0432\u0440\u044a\u0437\u043a\u0430'
grpSharedGroup = u'Shared Group'
grpSkypeFriends = u'Skype \u041f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
grpSkypeOutFriends = u'SkypeOut \u041f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
grpUngroupedFriends = u'\u041d\u0435\u0433\u0440\u0443\u043f\u0438\u0440\u0430\u043d\u0438 \u041f\u0440\u0438\u044f\u0442\u0435\u043b\u0438'
grpUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
grpUsersAuthorizedByMe = u'\u041e\u0442\u043e\u0440\u0438\u0437\u0438\u0440\u0430\u043d\u0438 \u043e\u0442 \u043c\u0435\u043d'
grpUsersBlockedByMe = u'\u0411\u043b\u043e\u043a\u0438\u0440\u0430\u043d\u0438 \u043e\u0442 \u043c\u0435\u043d'
grpUsersWaitingMyAuthorization = u'\u0427\u0430\u043a\u0430\u0449\u0438 \u043c\u043e\u044f\u0442\u0430 \u043e\u0442\u043e\u0440\u0438\u0437\u0430\u0446\u0438\u044f'
leaAddDeclined = u'\u0414\u043e\u0431\u0430\u0432\u044f\u043d\u0435\u0442\u043e \u043e\u0442\u043a\u0430\u0437\u0430\u043d\u043e'
leaAddedNotAuthorized = u'\u0414\u043e\u0431\u044f\u0432\u0430\u043d\u0438\u044f\u0442 \u0442\u0440\u044f\u0431\u0432\u0430 \u0434\u0430 \u0435 \u043e\u0442\u043e\u0440\u0438\u0437\u0438\u0440\u0430\u043d'
leaAdderNotFriend = u'\u0414\u043e\u0431\u0430\u0432\u044f\u0449\u0438\u044f\u0442 \u0442\u0440\u044f\u0431\u0432\u0430 \u0434\u0430 \u0435 \u041f\u0440\u0438\u044f\u0442\u0435\u043b'
leaUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
leaUnsubscribe = u'\u041d\u0435 \u0435 \u0430\u0431\u043e\u043d\u0430\u0442'
leaUserIncapable = u'\u0410\u0431\u043e\u043d\u0430\u0442\u044a\u0442 \u043d\u044f\u043c\u0430 \u0432\u044a\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442 \u0437\u0430 \u0432\u0440\u044a\u0437\u043a\u0430'
leaUserNotFound = u'\u0410\u0431\u043e\u043d\u0430\u0442\u044a\u0442 \u043d\u0435 \u0435 \u043d\u0430\u043c\u0435\u0440\u0435\u043d'
olsAway = u'\u041e\u0442\u0441\u044a\u0441\u0442\u0432\u0430\u0449'
olsDoNotDisturb = u'\u041e\u0442\u043f\u043e\u0447\u0438\u0432\u0430\u0449'
olsNotAvailable = u'\u041d\u0435\u0434\u043e\u0441\u0442\u044a\u043f\u0435\u043d'
olsOffline = u'\u0418\u0437\u0432\u044a\u043d \u043b\u0438\u043d\u0438\u044f'
olsOnline = u'\u041d\u0430 \u043b\u0438\u043d\u0438\u044f'
olsSkypeMe = u'\u0421\u043a\u0430\u0439\u043f\u0432\u0430\u0449'
olsSkypeOut = u'SkypeOut'
olsUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
smsMessageStatusComposing = u'Composing'
smsMessageStatusDelivered = u'Delivered'
smsMessageStatusFailed = u'Failed'
smsMessageStatusRead = u'Read'
smsMessageStatusReceived = u'Received'
smsMessageStatusSendingToServer = u'Sending to Server'
smsMessageStatusSentToServer = u'Sent to Server'
smsMessageStatusSomeTargetsFailed = u'Some Targets Failed'
smsMessageStatusUnknown = u'Unknown'
smsMessageTypeCCRequest = u'Confirmation Code Request'
smsMessageTypeCCSubmit = u'Confirmation Code Submit'
smsMessageTypeIncoming = u'Incoming'
smsMessageTypeOutgoing = u'Outgoing'
smsMessageTypeUnknown = u'Unknown'
smsTargetStatusAcceptable = u'Acceptable'
smsTargetStatusAnalyzing = u'Analyzing'
smsTargetStatusDeliveryFailed = u'Delivery Failed'
smsTargetStatusDeliveryPending = u'Delivery Pending'
smsTargetStatusDeliverySuccessful = u'Delivery Successful'
smsTargetStatusNotRoutable = u'Not Routable'
smsTargetStatusUndefined = u'Undefined'
smsTargetStatusUnknown = u'Unknown'
usexFemale = u'\u0436\u0435\u043d\u0441\u043a\u0438'
usexMale = u'\u043c\u044a\u0436\u043a\u0438'
usexUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
vmrConnectError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u0441\u0432\u044a\u0440\u0437\u0432\u0430\u043d\u0435\u0442\u043e'
vmrFileReadError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u0447\u0435\u0442\u0435\u043d\u0435 \u043d\u0430 \u0444\u0430\u0439\u043b\u0430'
vmrFileWriteError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u0437\u0430\u043f\u0438\u0441 \u043d\u0430 \u0444\u0430\u0439\u043b\u0430'
vmrMiscError = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430 \u0433\u0440\u0435\u0448\u043a\u0430'
vmrNoError = u'\u041d\u044f\u043c\u0430 \u0433\u0440\u0435\u0448\u043a\u0430'
vmrNoPrivilege = u'\u041d\u044f\u043c\u0430 \u043f\u0440\u0438\u0432\u0438\u043b\u0435\u0433\u0438\u044f \u0437\u0430 \u0433\u043b\u0430\u0441\u043e\u0432\u0430 \u043f\u043e\u0449\u0430'
vmrNoVoicemail = u'\u041d\u044f\u043c\u0430 \u0442\u0430\u043a\u0430\u0432\u0430 \u0433\u043b\u0430\u0441\u043e\u0432\u0430 \u043f\u043e\u0449\u0430'
vmrPlaybackError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u043f\u0440\u043e\u0441\u043b\u0443\u0448\u0432\u0430\u043d\u0435'
vmrRecordingError = u'\u0413\u0440\u0435\u0448\u043a\u0430 \u043f\u0440\u0438 \u0437\u0430\u043f\u0438\u0441'
vmrUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
vmsBlank = u'\u041f\u0440\u0430\u0437\u043d\u0430'
vmsBuffering = u'\u0411\u0443\u0444\u0435\u0440\u0438\u0440\u0430\u043d\u0435'
vmsDeleting = u'\u0418\u0437\u0442\u0440\u0438\u0432\u0430\u043d\u0435'
vmsDownloading = u'\u0421\u0432\u0430\u043b\u044f\u043d\u0435'
vmsFailed = u'\u041d\u0435\u0443\u0441\u043f\u0435\u0448\u043d\u0430'
vmsNotDownloaded = u'\u041d\u0435 \u0435 \u0441\u0432\u0430\u043b\u0435\u043d\u0430'
vmsPlayed = u'\u041f\u0440\u043e\u0441\u043b\u0443\u0448\u0430\u043d\u0430'
vmsPlaying = u'\u041f\u0440\u043e\u0441\u043b\u0443\u0448\u0432\u0430\u043d\u0435'
vmsRecorded = u'\u0417\u0430\u043f\u0438\u0441\u0430\u043d\u0430'
vmsRecording = u'\u0417\u0430\u043f\u0438\u0441 \u043d\u0430 \u0433\u043b\u0430\u0441\u043e\u0432\u043e \u0441\u044a\u043e\u0431\u0449\u0435\u043d\u0438\u0435'
vmsUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
vmsUnplayed = u'\u041d\u0435 \u0435 \u043f\u0440\u043e\u0441\u043b\u0443\u0448\u0430\u043d\u0430'
vmsUploaded = u'\u041a\u0430\u0447\u0435\u043d\u0430'
vmsUploading = u'\u041a\u0430\u0447\u0432\u0430\u043d\u0435'
vmtCustomGreeting = u'\u041f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0438\u0437\u0438\u0440\u0430\u043d \u043f\u043e\u0437\u0434\u0440\u0430\u0432'
vmtDefaultGreeting = u'\u041f\u043e\u0437\u0434\u0440\u0430\u0432 \u043f\u043e \u043f\u043e\u0434\u0440\u0430\u0437\u0431\u0438\u0440\u0430\u043d\u0435'
vmtIncoming = u'\u0432\u0445\u043e\u0434\u044f\u0449\u043e \u0433\u043b\u0430\u0441\u043e\u0432\u043e \u0441\u044a\u043e\u0431\u0449\u0435\u043d\u0438\u0435'
vmtOutgoing = u'\u0418\u0437\u0445\u043e\u0434\u044f\u0449\u0430'
vmtUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
vssAvailable = u'\u0414\u043e\u0441\u0442\u044a\u043f\u0435\u043d'
vssNotAvailable = u'\u041d\u0435\u0434\u043e\u0441\u0442\u044a\u043f\u0435\u043d'
vssPaused = u'\u0412 \u043f\u0430\u0443\u0437\u0430'
vssRejected = u'\u041e\u0442\u0445\u0432\u044a\u0440\u043b\u0435\u043d\u043e'
vssRunning = u'\u041f\u0440\u043e\u0442\u0438\u0447\u0430'
vssStarting = u'\u0417\u0430\u043f\u043e\u0447\u0432\u0430'
vssStopping = u'\u041f\u0440\u0438\u043a\u043b\u044e\u0447\u0432\u0430'
vssUnknown = u'\u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u0430'
| 99.579787 | 268 | 0.793921 | 2,729 | 18,721 | 5.446317 | 0.098204 | 0.049788 | 0.024423 | 0.033641 | 0.624773 | 0.589719 | 0.561932 | 0.50259 | 0.457041 | 0.40732 | 0 | 0.477116 | 0.052294 | 18,721 | 187 | 269 | 100.112299 | 0.360613 | 0 | 0 | 0 | 0 | 0.406417 | 0.776465 | 0.69332 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
9fde67fb91abb7b7f56c2e169b8b828fe797150e | 686 | py | Python | happyplace/blog/views.py | RifatPiyal/HappyPlace | ee0be2595644fb67b7ebfb591b2ce2e28da06f7b | [
"MIT"
] | null | null | null | happyplace/blog/views.py | RifatPiyal/HappyPlace | ee0be2595644fb67b7ebfb591b2ce2e28da06f7b | [
"MIT"
] | 3 | 2019-12-22T20:19:33.000Z | 2019-12-22T20:20:36.000Z | happyplace/blog/views.py | RifatPiyal/HappyPlace | ee0be2595644fb67b7ebfb591b2ce2e28da06f7b | [
"MIT"
] | null | null | null | from django.shortcuts import render
def home(request):
return render(request, 'blog/index.html')
def about(request):
return render(request, 'blog/about.html')
def contact(request):
return render(request, 'blog/Contact.html')
def FAQ(request):
return render(request, 'blog/FAQ.html')
def advice(request):
return render(request, 'blog/advice.html')
def login(request):
return render(request, 'blog/login.html')
def dashboard(request):
return render(request, 'blog/dashboard.html')
def c_dashboard(request):
return render(request, 'blog/Cdashboard.html')
def loginCounselor(request):
return render(request, 'blog/loginCounselor.html')
| 18.052632 | 54 | 0.717201 | 87 | 686 | 5.643678 | 0.241379 | 0.238289 | 0.348269 | 0.476578 | 0.586558 | 0.158859 | 0 | 0 | 0 | 0 | 0 | 0 | 0.150146 | 686 | 37 | 55 | 18.540541 | 0.842196 | 0 | 0 | 0 | 0 | 0 | 0.22449 | 0.034985 | 0 | 0 | 0 | 0 | 0 | 1 | 0.473684 | false | 0 | 0.052632 | 0.473684 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
b04683d525df3195d599132a1139db55911a5dd5 | 36 | py | Python | pylibs/dynomite/__init__.py | moonpolysoft/dynomite | a5618dcbe17b16cefdc9c567f27a1f4445aee005 | [
"BSD-3-Clause"
] | 64 | 2015-01-27T08:31:08.000Z | 2022-01-01T20:41:26.000Z | pylibs/dynomite/__init__.py | jpellerin/dynomite | 54bf80ae124bfef363fdd93468a6f8a6e154c37c | [
"BSD-3-Clause"
] | null | null | null | pylibs/dynomite/__init__.py | jpellerin/dynomite | 54bf80ae124bfef363fdd93468a6f8a6e154c37c | [
"BSD-3-Clause"
] | 15 | 2015-03-19T18:55:02.000Z | 2018-11-27T15:34:09.000Z | from dynomite.client import Client
| 12 | 34 | 0.833333 | 5 | 36 | 6 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.138889 | 36 | 2 | 35 | 18 | 0.967742 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
b04a142280ffd3ad80e47af61544e0958a68e94d | 26 | py | Python | tests/__init__.py | Agitive/django-push-notifications | cb54770ee5703a51067939cee170a9d3e62d8701 | [
"MIT"
] | 3 | 2017-05-06T11:21:19.000Z | 2018-01-10T22:38:30.000Z | netbox/secrets/tests/__init__.py | Cloudxtreme/netbox | 96d6be36080052122105583436e841997a5476cc | [
"Apache-2.0"
] | 1 | 2019-06-29T17:08:47.000Z | 2019-06-29T17:08:47.000Z | netbox/secrets/tests/__init__.py | Cloudxtreme/netbox | 96d6be36080052122105583436e841997a5476cc | [
"Apache-2.0"
] | 4 | 2017-02-01T22:53:14.000Z | 2017-06-22T18:05:03.000Z | from test_models import *
| 13 | 25 | 0.807692 | 4 | 26 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.153846 | 26 | 1 | 26 | 26 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
b054d2181edf60e57273a8a13d577310b286f991 | 48 | py | Python | cvh/__init__.py | AkshayHolkar/cvh | 2d35c6f0745fda69564ae1a15d1cc6fa8b709a17 | [
"MIT"
] | null | null | null | cvh/__init__.py | AkshayHolkar/cvh | 2d35c6f0745fda69564ae1a15d1cc6fa8b709a17 | [
"MIT"
] | null | null | null | cvh/__init__.py | AkshayHolkar/cvh | 2d35c6f0745fda69564ae1a15d1cc6fa8b709a17 | [
"MIT"
] | null | null | null | from cvh.HandTrackingModule import HandDetector
| 24 | 47 | 0.895833 | 5 | 48 | 8.6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083333 | 48 | 1 | 48 | 48 | 0.977273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c66303705c749da77f9380bf71b76dddd5d82fae | 265 | py | Python | arekit/contrib/networks/core/params.py | nicolay-r/AREk | 19c39ec0dc9a17464cade03b9c4da0c6d1d21191 | [
"MIT"
] | 18 | 2019-12-14T18:43:11.000Z | 2022-03-21T05:55:36.000Z | arekit/contrib/networks/core/params.py | nicolay-r/AREk | 19c39ec0dc9a17464cade03b9c4da0c6d1d21191 | [
"MIT"
] | 284 | 2020-08-08T20:52:44.000Z | 2022-03-31T05:26:20.000Z | arekit/contrib/networks/core/params.py | nicolay-r/AREk | 19c39ec0dc9a17464cade03b9c4da0c6d1d21191 | [
"MIT"
] | 1 | 2021-08-07T13:17:43.000Z | 2021-08-07T13:17:43.000Z | from arekit.common.model.params import BaseModelParams
class NeuralNetworkModelParams(BaseModelParams):
def __init__(self, epochs_count):
self.__epochs_count = epochs_count
@property
def EpochsCount(self):
return self.__epochs_count
| 22.083333 | 54 | 0.750943 | 28 | 265 | 6.678571 | 0.607143 | 0.235294 | 0.240642 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184906 | 265 | 11 | 55 | 24.090909 | 0.865741 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.142857 | 0.142857 | 0.714286 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
c6923c23adbe4ee592c962ed05aa3c98359c7cfa | 176 | py | Python | src/bpp/tests/tests_legacy/test_reports/__init__.py | iplweb/django-bpp | 85f183a99d8d5027ae4772efac1e4a9f21675849 | [
"BSD-3-Clause"
] | 1 | 2017-04-27T19:50:02.000Z | 2017-04-27T19:50:02.000Z | src/bpp/tests/tests_legacy/test_reports/__init__.py | mpasternak/django-bpp | 434338821d5ad1aaee598f6327151aba0af66f5e | [
"BSD-3-Clause"
] | 41 | 2019-11-07T00:07:02.000Z | 2022-02-27T22:09:39.000Z | src/bpp/tests/tests_legacy/test_reports/__init__.py | iplweb/bpp | f027415cc3faf1ca79082bf7bacd4be35b1a6fdf | [
"BSD-3-Clause"
] | null | null | null | # -*- encoding: utf-8 -*-
#
#from .test_komisja_centralna import *
#from .test_kronika_uczelni import *
#from .test_opi2012 import *
#from .test_raport_jednostek_2012 import *
| 25.142857 | 42 | 0.75 | 23 | 176 | 5.391304 | 0.608696 | 0.258065 | 0.33871 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.058442 | 0.125 | 176 | 6 | 43 | 29.333333 | 0.746753 | 0.926136 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
c6a388fdfce832af516df36b323f75fa41eed54b | 59 | py | Python | performance/driver/classes/observer/logstax/__init__.py | mesosphere/dcos-perf-test-driver | 8fba87cb6c6f64690c0b5bef5c7d9f2aa0fba06b | [
"Apache-2.0"
] | 2 | 2018-02-27T18:21:21.000Z | 2018-03-16T12:12:12.000Z | performance/driver/classes/observer/logstax/__init__.py | mesosphere/dcos-perf-test-driver | 8fba87cb6c6f64690c0b5bef5c7d9f2aa0fba06b | [
"Apache-2.0"
] | 1 | 2018-06-25T07:14:41.000Z | 2018-06-25T07:14:41.000Z | performance/driver/classes/observer/logstax/__init__.py | mesosphere/dcos-perf-test-driver | 8fba87cb6c6f64690c0b5bef5c7d9f2aa0fba06b | [
"Apache-2.0"
] | 1 | 2020-06-25T10:37:21.000Z | 2020-06-25T10:37:21.000Z | from .observer import LogStaxObserver, LogStaxMessageEvent
| 29.5 | 58 | 0.881356 | 5 | 59 | 10.4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.084746 | 59 | 1 | 59 | 59 | 0.962963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c6ab6e3d35f52ccae1d178dad2dd93da2fac63ef | 21 | py | Python | one.py | akshaynagpal/data_science | a525ff87f737afa9a2abee27c506663f19396999 | [
"MIT"
] | null | null | null | one.py | akshaynagpal/data_science | a525ff87f737afa9a2abee27c506663f19396999 | [
"MIT"
] | null | null | null | one.py | akshaynagpal/data_science | a525ff87f737afa9a2abee27c506663f19396999 | [
"MIT"
] | null | null | null | from pandas import *
| 10.5 | 20 | 0.761905 | 3 | 21 | 5.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.190476 | 21 | 1 | 21 | 21 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
05c456bc3f6a17a27b68abfd2686269253aa19d6 | 108 | py | Python | config/default.py | hmrc/wristband-frontend | a2e9e0138dc5840215c8b17384deb5b70b540c1c | [
"Apache-2.0"
] | 2 | 2016-04-06T11:29:29.000Z | 2018-03-26T12:49:07.000Z | config/default.py | hmrc/wristband-frontend | a2e9e0138dc5840215c8b17384deb5b70b540c1c | [
"Apache-2.0"
] | 1 | 2015-09-09T09:05:19.000Z | 2015-09-09T09:05:19.000Z | config/default.py | hmrc/wristband-frontend | a2e9e0138dc5840215c8b17384deb5b70b540c1c | [
"Apache-2.0"
] | 7 | 2015-10-28T18:56:47.000Z | 2021-04-10T23:51:50.000Z | import os
WTF_CSRF_ENABLED = False
PASSWORD_RESET_MESSAGE = os.environ.get("PASSWORD_RESET_MESSAGE", None)
| 21.6 | 71 | 0.824074 | 16 | 108 | 5.1875 | 0.75 | 0.313253 | 0.481928 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.092593 | 108 | 4 | 72 | 27 | 0.846939 | 0 | 0 | 0 | 0 | 0 | 0.203704 | 0.203704 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.333333 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 6 |
05f0ed4cb664a576f80e612919c64c5c15b149dc | 383 | py | Python | rastervision/data/api.py | carderne/raster-vision | 915fbcd3263d8f2193e65c2cd0eb53e050a47a01 | [
"Apache-2.0"
] | 4 | 2019-03-11T12:38:15.000Z | 2021-04-06T14:57:52.000Z | rastervision/data/api.py | carderne/raster-vision | 915fbcd3263d8f2193e65c2cd0eb53e050a47a01 | [
"Apache-2.0"
] | null | null | null | rastervision/data/api.py | carderne/raster-vision | 915fbcd3263d8f2193e65c2cd0eb53e050a47a01 | [
"Apache-2.0"
] | 1 | 2020-04-27T15:21:53.000Z | 2020-04-27T15:21:53.000Z | # flake8: noqa
from rastervision.data.raster_source.api import *
from rastervision.data.raster_transformer.api import *
from rastervision.data.label_source.api import *
from rastervision.data.label_store.api import *
from rastervision.data.vector_source.api import *
from rastervision.data.dataset_config import DatasetConfig
from rastervision.data.scene_config import SceneConfig
| 34.818182 | 58 | 0.845953 | 51 | 383 | 6.215686 | 0.352941 | 0.353312 | 0.44164 | 0.394322 | 0.545741 | 0.454259 | 0 | 0 | 0 | 0 | 0 | 0.002857 | 0.086162 | 383 | 10 | 59 | 38.3 | 0.902857 | 0.031332 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
af1274f444e1543d83b4a4f751e49a382a372249 | 44 | py | Python | opensenate/__init__.py | g0ulartleo/opendata-senado | 091d060d55d49f844d192baa1c0aef1aa039f1c0 | [
"MIT"
] | null | null | null | opensenate/__init__.py | g0ulartleo/opendata-senado | 091d060d55d49f844d192baa1c0aef1aa039f1c0 | [
"MIT"
] | null | null | null | opensenate/__init__.py | g0ulartleo/opendata-senado | 091d060d55d49f844d192baa1c0aef1aa039f1c0 | [
"MIT"
] | null | null | null | from .parliamentarians import SenatorClient
| 22 | 43 | 0.886364 | 4 | 44 | 9.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 44 | 1 | 44 | 44 | 0.975 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
af4c629133a0d65696ef7f10f65d9ac889519976 | 29 | py | Python | messaging_components/brokers/artemis/__init__.py | fgiorgetti/qpid-dispatch-tests | 164c609d28db87692eed53d5361aa1ee5c97375c | [
"Apache-2.0"
] | null | null | null | messaging_components/brokers/artemis/__init__.py | fgiorgetti/qpid-dispatch-tests | 164c609d28db87692eed53d5361aa1ee5c97375c | [
"Apache-2.0"
] | null | null | null | messaging_components/brokers/artemis/__init__.py | fgiorgetti/qpid-dispatch-tests | 164c609d28db87692eed53d5361aa1ee5c97375c | [
"Apache-2.0"
] | null | null | null | from .artemis import Artemis
| 14.5 | 28 | 0.827586 | 4 | 29 | 6 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.137931 | 29 | 1 | 29 | 29 | 0.96 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
af60216e7db089575aeb7287242ea1be9eb88e3e | 96 | py | Python | venv/lib/python3.8/site-packages/parso/__init__.py | GiulianaPola/select_repeats | 17a0d053d4f874e42cf654dd142168c2ec8fbd11 | [
"MIT"
] | 2 | 2022-03-13T01:58:52.000Z | 2022-03-31T06:07:54.000Z | venv/lib/python3.8/site-packages/parso/__init__.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | 19 | 2021-11-20T04:09:18.000Z | 2022-03-23T15:05:55.000Z | venv/lib/python3.8/site-packages/parso/__init__.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | null | null | null | /home/runner/.cache/pip/pool/43/ac/58/7ad9dff88c7e82f987d7be3d371c302446b66609f3c941072f0f564484 | 96 | 96 | 0.895833 | 9 | 96 | 9.555556 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.458333 | 0 | 96 | 1 | 96 | 96 | 0.4375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
af639911152b571ad0bf298695f30bc73023d19c | 30 | py | Python | forecastio/__init__.py | vIiRuS/pisst.es | 47c116417ab30a880f517b8208d0ecdbb74d0404 | [
"Apache-2.0"
] | null | null | null | forecastio/__init__.py | vIiRuS/pisst.es | 47c116417ab30a880f517b8208d0ecdbb74d0404 | [
"Apache-2.0"
] | null | null | null | forecastio/__init__.py | vIiRuS/pisst.es | 47c116417ab30a880f517b8208d0ecdbb74d0404 | [
"Apache-2.0"
] | null | null | null | from api import load_forecast
| 15 | 29 | 0.866667 | 5 | 30 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 30 | 1 | 30 | 30 | 0.961538 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
af7025c9fb68c7da316f687b73567c7b1df8331f | 24 | py | Python | src/wrant/__init__.py | fran-mora/wrant | 6dc5ed7e6744c2fbcb6b82f51fbebbaea230977b | [
"MIT"
] | null | null | null | src/wrant/__init__.py | fran-mora/wrant | 6dc5ed7e6744c2fbcb6b82f51fbebbaea230977b | [
"MIT"
] | 2 | 2018-04-15T11:50:01.000Z | 2018-04-15T11:50:52.000Z | src/wrant/__init__.py | fm2g11/wrant | 6dc5ed7e6744c2fbcb6b82f51fbebbaea230977b | [
"MIT"
] | null | null | null | from .wrant import Wrant | 24 | 24 | 0.833333 | 4 | 24 | 5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 24 | 1 | 24 | 24 | 0.952381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
af76e4e71d4ce32c893683acec7abe7be9ebc1af | 1,939 | py | Python | statistic/migrations/0001_initial.py | OnGridSystems/RobotVeraWebApp | 01cee658a3983fcaf128b40bb99c1a4272e90c07 | [
"MIT"
] | 11 | 2018-06-13T10:10:11.000Z | 2021-06-05T08:23:43.000Z | statistic/migrations/0001_initial.py | OnGridSystems/RobotVeraWebApp | 01cee658a3983fcaf128b40bb99c1a4272e90c07 | [
"MIT"
] | 5 | 2021-03-19T23:41:21.000Z | 2022-03-12T00:37:18.000Z | statistic/migrations/0001_initial.py | OnGridSystems/RobotVeraWebApp | 01cee658a3983fcaf128b40bb99c1a4272e90c07 | [
"MIT"
] | 5 | 2018-08-17T16:09:33.000Z | 2021-06-06T05:32:10.000Z | # Generated by Django 2.0.4 on 2018-07-30 10:20
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='CvStatistic',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('role', models.CharField(max_length=25)),
('role_obj_id', models.PositiveIntegerField(blank=True, default=None, null=True)),
('obj_id', models.PositiveIntegerField()),
('ip', models.GenericIPAddressField()),
('session_id', models.CharField(max_length=32)),
('count', models.PositiveIntegerField(default=1)),
('date_created', models.DateTimeField(auto_now_add=True)),
('date_updated', models.DateTimeField(auto_now=True)),
],
options={
'verbose_name': 'CV statistic',
},
),
migrations.CreateModel(
name='VacancyStatistic',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('role', models.CharField(max_length=25)),
('role_obj_id', models.PositiveIntegerField(blank=True, default=None, null=True)),
('obj_id', models.PositiveIntegerField()),
('ip', models.GenericIPAddressField()),
('session_id', models.CharField(max_length=32)),
('count', models.PositiveIntegerField(default=1)),
('date_created', models.DateTimeField(auto_now_add=True)),
('date_updated', models.DateTimeField(auto_now=True)),
],
options={
'verbose_name': 'Vacancy statistic',
},
),
]
| 39.571429 | 114 | 0.560083 | 176 | 1,939 | 6 | 0.357955 | 0.060606 | 0.068182 | 0.090909 | 0.774621 | 0.774621 | 0.774621 | 0.774621 | 0.774621 | 0.774621 | 0 | 0.018532 | 0.304281 | 1,939 | 48 | 115 | 40.395833 | 0.76427 | 0.023208 | 0 | 0.682927 | 1 | 0 | 0.112051 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.02439 | 0 | 0.121951 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
bb6c7bae6eefd5f5b8aa055bb5fae69784e1b287 | 47 | py | Python | gym_tree/envs/__init__.py | mhun1/gym_tree | c24e9f4c959b7c44a75d47f69b3cba9cfd1a3fdc | [
"MIT"
] | null | null | null | gym_tree/envs/__init__.py | mhun1/gym_tree | c24e9f4c959b7c44a75d47f69b3cba9cfd1a3fdc | [
"MIT"
] | null | null | null | gym_tree/envs/__init__.py | mhun1/gym_tree | c24e9f4c959b7c44a75d47f69b3cba9cfd1a3fdc | [
"MIT"
] | null | null | null | from gym_tree.envs.tree_env import LearningEnv
| 23.5 | 46 | 0.87234 | 8 | 47 | 4.875 | 0.875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.085106 | 47 | 1 | 47 | 47 | 0.906977 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
bba26a4d432452356dfa3935a73254e1453401ed | 85 | py | Python | __init__.py | FEEprojects/sensirionpycom | 6a7fdcd614ca297024af0ccd42faef9f4797f25f | [
"MIT"
] | 6 | 2019-08-07T13:56:43.000Z | 2020-11-01T02:58:51.000Z | __init__.py | FEEprojects/sensirionpycom | 6a7fdcd614ca297024af0ccd42faef9f4797f25f | [
"MIT"
] | 78 | 2020-03-20T13:58:10.000Z | 2021-07-29T08:24:57.000Z | __init__.py | FEEprojects/sensirionpycom | 6a7fdcd614ca297024af0ccd42faef9f4797f25f | [
"MIT"
] | 5 | 2019-08-08T10:23:35.000Z | 2021-10-06T18:34:03.000Z | from sensirionpycom.sensirion import SensirionReading, Sensirion, SensirionException
| 42.5 | 84 | 0.894118 | 7 | 85 | 10.857143 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.070588 | 85 | 1 | 85 | 85 | 0.962025 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
bba3906d58197b0fa98d7ffacc2b7c48c910824b | 120 | py | Python | api/admin.py | mark-barrett/RESTBroker | d9b0a3574d2970443fdf40c70ab9ceb8d72614f4 | [
"MIT"
] | null | null | null | api/admin.py | mark-barrett/RESTBroker | d9b0a3574d2970443fdf40c70ab9ceb8d72614f4 | [
"MIT"
] | null | null | null | api/admin.py | mark-barrett/RESTBroker | d9b0a3574d2970443fdf40c70ab9ceb8d72614f4 | [
"MIT"
] | null | null | null | from django.contrib import admin
from api.models import *
admin.site.register(APIKey)
admin.site.register(APIRequest)
| 17.142857 | 32 | 0.808333 | 17 | 120 | 5.705882 | 0.647059 | 0.226804 | 0.350515 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 120 | 6 | 33 | 20 | 0.898148 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
a5886f9c1b01a8b897758d0692fe3d5290d3febc | 5,948 | py | Python | tests/test_linops/test_linops_cases/kronecker_cases.py | fxbriol/probnum | 7e0e94cf9146aaa2b730b02c6d75a022cd629b5c | [
"MIT"
] | 1 | 2022-03-30T20:16:13.000Z | 2022-03-30T20:16:13.000Z | tests/test_linops/test_linops_cases/kronecker_cases.py | fxbriol/probnum | 7e0e94cf9146aaa2b730b02c6d75a022cd629b5c | [
"MIT"
] | null | null | null | tests/test_linops/test_linops_cases/kronecker_cases.py | fxbriol/probnum | 7e0e94cf9146aaa2b730b02c6d75a022cd629b5c | [
"MIT"
] | null | null | null | import itertools
from typing import Tuple, Union
import numpy as np
import pytest
import pytest_cases
import probnum as pn
from probnum.problems.zoo.linalg import random_spd_matrix
spd_matrices = (
pn.linops.Identity(shape=(1, 1)),
np.array([[1.0, -2.0], [-2.0, 5.0]]),
random_spd_matrix(np.random.default_rng(597), dim=9),
)
@pytest.mark.parametrize(
"A,B",
[
(np.array([[2, -3.5], [12, 6.5]]), np.eye(3)),
(np.array([[1, -2], [-2.2, 5]]), np.array([[1, -3], [0, -0.5]])),
(np.array([[4, 1, 4], [2, 3, 2]]), np.array([[-1, 4], [2, 1]])),
(np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9]]), np.array([[1, 4]])),
(np.array([[4, 1], [2, 3]]), np.array([[-1, 4], [2, 1]])),
(
np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9], [1, 0, 2]]),
np.array([[1, 4, 0], [-3, -0.4, -100], [0.18, -2, 10]]),
),
(
np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9], [1, 0, 2]]),
np.array([[1, 4, 0], [-3, -0.4, -100]]),
),
],
)
def case_kronecker(
A: np.ndarray, B: np.ndarray
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
linop = pn.linops.Kronecker(A, B)
matrix = np.kron(A, B)
return linop, matrix
@pytest_cases.case(tags=["square", "singular"])
@pytest_cases.parametrize(
"A,B",
[
(
np.random.default_rng(78923 + m + n).uniform(0.9, 1.1, (m, n)),
np.full((n, m), np.random.default_rng(25789 + m + n).uniform(0.9, 1.1)),
)
for m, n in ((3, 4), (1, 8), (2, 3))
],
)
def case_kronecker_square_non_square_factors(
A: np.ndarray, B: np.ndarray
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
linop = pn.linops.Kronecker(A, B)
matrix = np.kron(A, B)
return linop, matrix
@pytest_cases.case(tags=["square", "symmetric", "positive-definite"])
@pytest_cases.parametrize("A,B", itertools.product(spd_matrices, spd_matrices))
def case_kronecker_positive_definite(
A: Union[np.ndarray, pn.linops.LinearOperator],
B: Union[np.ndarray, pn.linops.LinearOperator],
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
A = pn.linops.aslinop(A)
A.is_symmetric = True
B = pn.linops.aslinop(B)
B.is_symmetric = True
linop = pn.linops.Kronecker(A, B)
matrix = np.kron(A.todense(), B.todense())
return linop, matrix
@pytest.mark.parametrize(
"A,B",
[
(np.array([[1, -2], [-2.2, 5]]), np.array([[1, -3], [0, -0.5]])),
(np.array([[4, 1], [2, 3]]), np.array([[-1, 4], [2, 1]])),
(
np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9], [1, 0, 2]]),
np.array([[1, 4, 0], [-3, -0.4, -100], [0.18, -2, 10]]),
),
],
)
@pytest_cases.case(tags=["symmetric_kronecker"])
def case_symmetric_kronecker(
A: np.ndarray, B: np.ndarray
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
linop = pn.linops.SymmetricKronecker(A, B)
matrix = (np.kron(A, B) + np.kron(B, A)) / 2
return linop, matrix
@pytest_cases.case(
tags=["symmetric_kronecker", "square", "symmetric", "positive-definite"]
)
@pytest_cases.parametrize(
"A,B",
[
(
random_spd_matrix(np.random.default_rng(234789 + n), dim=n),
random_spd_matrix(np.random.default_rng(347892 + n), dim=n),
)
for n in [1, 2, 3, 6]
],
)
def case_symmetric_kronecker_positive_definite(
A: Union[np.ndarray, pn.linops.LinearOperator],
B: Union[np.ndarray, pn.linops.LinearOperator],
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
A = pn.linops.aslinop(A)
A.is_symmetric = True
B = pn.linops.aslinop(B)
B.is_symmetric = True
linop = pn.linops.SymmetricKronecker(A, B)
matrix = (np.kron(A.todense(), B.todense()) + np.kron(B.todense(), A.todense())) / 2
return linop, matrix
@pytest.mark.parametrize(
"A",
[
np.array([[1, -2], [-2.2, 5]]),
np.array([[1, -3], [0, -0.5]]),
np.array([[4, 1], [2, 3]]),
np.array([[-1, 4], [2, 1]]),
np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9], [1, 0, 2]]),
np.array([[1, 4, 0], [-3, -0.4, -100], [0.18, -2, 10]]),
],
)
@pytest_cases.case(tags=["symmetric_kronecker"])
def case_symmetric_kronecker_identical_factors(
A: np.ndarray,
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
linop = pn.linops.SymmetricKronecker(A)
matrix = np.kron(A, A)
return linop, matrix
@pytest_cases.case(
tags=[
"symmetric_kronecker",
"square",
"symmetric",
"positive-definite",
]
)
@pytest_cases.parametrize("A", spd_matrices)
def case_symmetric_kronecker_identical_factors_positive_definite(
A: Union[np.ndarray, pn.linops.LinearOperator],
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
A = pn.linops.aslinop(A)
A.is_symmetric = True
linop = pn.linops.SymmetricKronecker(A)
matrix = np.kron(A.todense(), A.todense())
return linop, matrix
@pytest_cases.case(tags=["square"])
@pytest_cases.parametrize("num_blocks", [1, 2, 3])
@pytest_cases.parametrize("B", [np.array([[0.4, 2, 0.8], [-0.4, 0, -0.9], [1, 0, 2]])])
def case_identity_kronecker_square(
num_blocks: int, B: Union[np.ndarray, pn.linops.LinearOperator]
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
linop = pn.linops.IdentityKronecker(num_blocks, B)
matrix = np.kron(np.eye(num_blocks, dtype=linop.dtype), B)
return linop, matrix
@pytest_cases.case(tags=["square", "symmetric", "positive-definite"])
@pytest_cases.parametrize("num_blocks", [1, 2, 3])
@pytest_cases.parametrize("B", spd_matrices)
def case_identity_kronecker_positive_definite(
num_blocks: int, B: Union[np.ndarray, pn.linops.LinearOperator]
) -> Tuple[pn.linops.LinearOperator, np.ndarray]:
B = pn.linops.aslinop(B)
B.is_symmetric = True
linop = pn.linops.IdentityKronecker(num_blocks, B)
matrix = np.kron(np.eye(num_blocks, dtype=linop.dtype), B.todense())
return linop, matrix
| 29.74 | 88 | 0.589442 | 885 | 5,948 | 3.865537 | 0.094915 | 0.074832 | 0.037416 | 0.023677 | 0.832797 | 0.813797 | 0.797135 | 0.728442 | 0.716165 | 0.684595 | 0 | 0.055943 | 0.203598 | 5,948 | 199 | 89 | 29.889447 | 0.666244 | 0 | 0 | 0.533742 | 0 | 0 | 0.044217 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.055215 | false | 0 | 0.042945 | 0 | 0.153374 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3c0c8347cc9ecc1d5af353b49d20e66076318b34 | 406 | py | Python | tests/test_tokenization.py | aflueckiger/impresso-text-acquisition | ed8f0586ed6a4f7de94b1504b292570bce1f51c5 | [
"MIT"
] | null | null | null | tests/test_tokenization.py | aflueckiger/impresso-text-acquisition | ed8f0586ed6a4f7de94b1504b292570bce1f51c5 | [
"MIT"
] | null | null | null | tests/test_tokenization.py | aflueckiger/impresso-text-acquisition | ed8f0586ed6a4f7de94b1504b292570bce1f51c5 | [
"MIT"
] | null | null | null | from text_importer.tokenization import insert_whitespace
def test_insert_whitespace():
assert insert_whitespace("Lausanne", ",", None, "fr") is False
assert insert_whitespace("(", "encore", None, "fr") is False
assert insert_whitespace(".", "01", "52", "fr") is False
assert insert_whitespace(",", "500", "000", "fr") is False
assert insert_whitespace(",", "500", None, "fr") is True
| 40.6 | 66 | 0.67734 | 51 | 406 | 5.215686 | 0.411765 | 0.421053 | 0.413534 | 0.225564 | 0.518797 | 0.518797 | 0.518797 | 0 | 0 | 0 | 0 | 0.037901 | 0.155172 | 406 | 9 | 67 | 45.111111 | 0.737609 | 0 | 0 | 0 | 0 | 0 | 0.103448 | 0 | 0 | 0 | 0 | 0 | 0.714286 | 1 | 0.142857 | true | 0 | 0.142857 | 0 | 0.285714 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3c5996b4355fd4371d51e2d1f65fd2ce4be6bc4f | 103 | py | Python | exoatlas/visualizations/panels/__init__.py | zkbt/exopop | 5e8b9d391fe9e2d39c623d7ccd7eca8fd0f0f3f8 | [
"MIT"
] | 4 | 2020-06-24T16:38:27.000Z | 2022-01-23T01:57:19.000Z | exoatlas/visualizations/panels/__init__.py | zkbt/exopop | 5e8b9d391fe9e2d39c623d7ccd7eca8fd0f0f3f8 | [
"MIT"
] | 4 | 2018-09-20T23:12:30.000Z | 2019-05-15T15:31:58.000Z | exoatlas/visualizations/panels/__init__.py | zkbt/exopop | 5e8b9d391fe9e2d39c623d7ccd7eca8fd0f0f3f8 | [
"MIT"
] | null | null | null | from .Panel import *
from .BubblePanel import *
from .ErrorPanel import *
from .preset_panels import *
| 20.6 | 28 | 0.76699 | 13 | 103 | 6 | 0.538462 | 0.384615 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.15534 | 103 | 4 | 29 | 25.75 | 0.896552 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
3c65fbe09c4b77a6ab0942bd0e0b7ce339728b2c | 8,607 | py | Python | test_output_handling.py | antonOO/vmware-openapi-generator-1 | f06cf93a683969e6a6fb9560f2e0a029bb769e89 | [
"MIT"
] | 19 | 2018-12-07T18:54:25.000Z | 2021-12-06T23:10:41.000Z | test_output_handling.py | antonOO/vmware-openapi-generator-1 | f06cf93a683969e6a6fb9560f2e0a029bb769e89 | [
"MIT"
] | 27 | 2019-01-07T08:38:36.000Z | 2021-04-28T15:52:51.000Z | test_output_handling.py | antonOO/vmware-openapi-generator-1 | f06cf93a683969e6a6fb9560f2e0a029bb769e89 | [
"MIT"
] | 19 | 2018-12-07T06:47:53.000Z | 2021-12-13T15:59:28.000Z | # Copyright 2020 VMware, Inc.
# SPDX-License-Identifier: MIT
import unittest
from lib.file_output_handler import SpecificationDictsMerger
class TestSpecificationDictsMerger(unittest.TestCase):
def test_merge_api_rest_dicts(self):
rest_path_dict = {"/rest/com/vmware/vcenter/ovf/library_item":
{"post": {
"tags": [
"ovf/library_item"
],
"parameters": [
{
"in": "body",
"name": "request_body",
"required": True,
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.library_item_create"
}
}
],
"responses": {
200: {
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.library_item.create_resp"
}
},
400: {
"description": "if the specified virtual machine or virtual appliance is busy.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.resource_busy_error"
}
},
404: {
"description": "if the virtual machine or virtual appliance specified by {@param.name source} does not exist.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.not_found_error"
}
}
},
"operationId": "create"
}
},
"/rest/com/vmware/vcenter/ovf/import_flag": {
"get": {
"tags": [
"ovf/import_flag"
],
"summary": "Returns information about the import flags supported by the deployment platform. <p> The supported flags are: <dl> <dt>LAX</dt> <dd>Lax mode parsing of the OVF descriptor.</dd> </dl> <p> Future server versions might support additional flags.",
"parameters": [
{
"type": "string",
"in": "query",
"name": "rp",
"description": "The identifier of resource pool target for retrieving the import flag(s).",
"required": True
}
],
"responses": {
200: {
"description": "A {@term list} of supported import flags.",
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.import_flag.list_resp"
}
},
404: {
"description": "If the resource pool associated with {@param.name rp} does not exist.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.not_found_error"
}
}
},
"operationId": "list"
}
}
}
rest_type_dict = {"com.vmware.vcenter.ovf.import_flag.list_resp": {
"type": "object",
"properties": {
"value": {
"type": "array",
"items": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.import_flag.info"
}
}
},
"required": [
"value"
]
}}
# Use copies rather than references to the same dict
api_path_dict = {
"/api/com/vmware/vcenter/ovf/library_item": {"post": {
"tags": [
"ovf/library_item"
],
"parameters": [
{
"in": "body",
"name": "request_body",
"required": True,
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.library_item_create"
}
}
],
"responses": {
200: {
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.library_item.create_resp"
}
},
400: {
"description": "if the specified virtual machine or virtual appliance is busy.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.resource_busy_error"
}
},
404: {
"description": "if the virtual machine or virtual appliance specified by {@param.name source} does not exist.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.not_found_error"
}
}
},
"operationId": "create"
}
},
"/api/com/vmware/vcenter/ovf/import_flag": {
"get": {
"tags": [
"ovf/import_flag"
],
"summary": "Returns information about the import flags supported by the deployment platform. <p> The supported flags are: <dl> <dt>LAX</dt> <dd>Lax mode parsing of the OVF descriptor.</dd> </dl> <p> Future server versions might support additional flags.",
"parameters": [
{
"type": "string",
"in": "query",
"name": "rp",
"description": "The identifier of resource pool target for retrieving the import flag(s).",
"required": True
}
],
"responses": {
200: {
"description": "A {@term list} of supported import flags.",
"schema": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.import_flag.list_resp"
}
},
404: {
"description": "If the resource pool associated with {@param.name rp} does not exist.",
"schema": {
"$ref": "#/definitions/com.vmware.vapi.std.errors.not_found_error"
}
}
},
"operationId": "list"
}
},
"/api/com/vmware/vcenter/ovf/export_flag": {}
}
api_type_dict = {"ComVmwareVcenterOvfImportFlag": {
"type": "object",
"properties": {
"value": {
"type": "array",
"items": {
"$ref": "#/definitions/com.vmware.vcenter.ovf.import_flag.info"
}
}
},
"required": [
"value"
]
}}
rest_spec = {"vcenter": (dict(rest_path_dict), dict(rest_type_dict)),
"appliance": ({}, {})}
api_spec = {"vcenter": (dict(api_path_dict), dict(api_type_dict)),
"cis": ({}, {})}
merger = SpecificationDictsMerger(dict(rest_spec), dict(api_spec))
merged = merger.merge_api_rest_dicts()
self.assertTrue("vcenter" in merged and "cis" in merged and "appliance" in merged)
self.assertEqual(len(merged["vcenter"][0]), 5)
self.assertEqual(len(merged["vcenter"][1]), 2)
api_def_type = merged["vcenter"][0] \
.get("/api/com/vmware/vcenter/ovf/import_flag") \
.get("get") \
.get("responses") \
.get(200) \
.get("schema") \
.get("$ref")
self.assertEqual(api_def_type, "#/definitions/com.vmware.vcenter.ovf.import_flag.list_resp")
if __name__ == '__main__':
unittest.main()
| 41.781553 | 275 | 0.396073 | 643 | 8,607 | 5.172628 | 0.22084 | 0.059531 | 0.076969 | 0.091401 | 0.808178 | 0.766987 | 0.766987 | 0.766987 | 0.744438 | 0.730006 | 0 | 0.009561 | 0.489601 | 8,607 | 205 | 276 | 41.985366 | 0.747553 | 0.012432 | 0 | 0.5625 | 0 | 0.010417 | 0.368762 | 0.137594 | 0 | 0 | 0 | 0 | 0.020833 | 1 | 0.005208 | false | 0 | 0.104167 | 0 | 0.114583 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3c7e80b9d40ab532b60ede564800671439e0b420 | 129,730 | py | Python | sdk/redis/azure-mgmt-redis/azure/mgmt/redis/models/_models_py3.py | vincenttran-msft/azure-sdk-for-python | 348b56f9f03eeb3f7b502eed51daf494ffff874d | [
"MIT"
] | 2,728 | 2015-01-09T10:19:32.000Z | 2022-03-31T14:50:33.000Z | sdk/redis/azure-mgmt-redis/azure/mgmt/redis/models/_models_py3.py | v-xuto/azure-sdk-for-python | 9c6296d22094c5ede410bc83749e8df8694ccacc | [
"MIT"
] | 17,773 | 2015-01-05T15:57:17.000Z | 2022-03-31T23:50:25.000Z | sdk/redis/azure-mgmt-redis/azure/mgmt/redis/models/_models_py3.py | v-xuto/azure-sdk-for-python | 9c6296d22094c5ede410bc83749e8df8694ccacc | [
"MIT"
] | 1,916 | 2015-01-19T05:05:41.000Z | 2022-03-31T19:36:44.000Z | # coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import datetime
from typing import Any, Dict, List, Optional, Union
from azure.core.exceptions import HttpResponseError
import msrest.serialization
from ._redis_management_client_enums import *
class CheckNameAvailabilityParameters(msrest.serialization.Model):
"""Parameters body to pass for resource name availability check.
All required parameters must be populated in order to send to Azure.
:ivar name: Required. Resource name.
:vartype name: str
:ivar type: Required. Resource type. The only legal value of this property for checking redis
cache name availability is 'Microsoft.Cache/redis'.
:vartype type: str
"""
_validation = {
'name': {'required': True},
'type': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
*,
name: str,
type: str,
**kwargs
):
"""
:keyword name: Required. Resource name.
:paramtype name: str
:keyword type: Required. Resource type. The only legal value of this property for checking
redis cache name availability is 'Microsoft.Cache/redis'.
:paramtype type: str
"""
super(CheckNameAvailabilityParameters, self).__init__(**kwargs)
self.name = name
self.type = type
class ErrorAdditionalInfo(msrest.serialization.Model):
"""The resource management error additional info.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar type: The additional info type.
:vartype type: str
:ivar info: The additional info.
:vartype info: any
"""
_validation = {
'type': {'readonly': True},
'info': {'readonly': True},
}
_attribute_map = {
'type': {'key': 'type', 'type': 'str'},
'info': {'key': 'info', 'type': 'object'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(ErrorAdditionalInfo, self).__init__(**kwargs)
self.type = None
self.info = None
class ErrorDetail(msrest.serialization.Model):
"""The error detail.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar code: The error code.
:vartype code: str
:ivar message: The error message.
:vartype message: str
:ivar target: The error target.
:vartype target: str
:ivar details: The error details.
:vartype details: list[~azure.mgmt.redis.models.ErrorDetail]
:ivar additional_info: The error additional info.
:vartype additional_info: list[~azure.mgmt.redis.models.ErrorAdditionalInfo]
"""
_validation = {
'code': {'readonly': True},
'message': {'readonly': True},
'target': {'readonly': True},
'details': {'readonly': True},
'additional_info': {'readonly': True},
}
_attribute_map = {
'code': {'key': 'code', 'type': 'str'},
'message': {'key': 'message', 'type': 'str'},
'target': {'key': 'target', 'type': 'str'},
'details': {'key': 'details', 'type': '[ErrorDetail]'},
'additional_info': {'key': 'additionalInfo', 'type': '[ErrorAdditionalInfo]'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(ErrorDetail, self).__init__(**kwargs)
self.code = None
self.message = None
self.target = None
self.details = None
self.additional_info = None
class ErrorResponse(msrest.serialization.Model):
"""Common error response for all Azure Resource Manager APIs to return error details for failed operations. (This also follows the OData error response format.).
:ivar error: The error object.
:vartype error: ~azure.mgmt.redis.models.ErrorDetail
"""
_attribute_map = {
'error': {'key': 'error', 'type': 'ErrorDetail'},
}
def __init__(
self,
*,
error: Optional["ErrorDetail"] = None,
**kwargs
):
"""
:keyword error: The error object.
:paramtype error: ~azure.mgmt.redis.models.ErrorDetail
"""
super(ErrorResponse, self).__init__(**kwargs)
self.error = error
class ExportRDBParameters(msrest.serialization.Model):
"""Parameters for Redis export operation.
All required parameters must be populated in order to send to Azure.
:ivar format: File format.
:vartype format: str
:ivar prefix: Required. Prefix to use for exported files.
:vartype prefix: str
:ivar container: Required. Container name to export to.
:vartype container: str
"""
_validation = {
'prefix': {'required': True},
'container': {'required': True},
}
_attribute_map = {
'format': {'key': 'format', 'type': 'str'},
'prefix': {'key': 'prefix', 'type': 'str'},
'container': {'key': 'container', 'type': 'str'},
}
def __init__(
self,
*,
prefix: str,
container: str,
format: Optional[str] = None,
**kwargs
):
"""
:keyword format: File format.
:paramtype format: str
:keyword prefix: Required. Prefix to use for exported files.
:paramtype prefix: str
:keyword container: Required. Container name to export to.
:paramtype container: str
"""
super(ExportRDBParameters, self).__init__(**kwargs)
self.format = format
self.prefix = prefix
self.container = container
class ImportRDBParameters(msrest.serialization.Model):
"""Parameters for Redis import operation.
All required parameters must be populated in order to send to Azure.
:ivar format: File format.
:vartype format: str
:ivar files: Required. files to import.
:vartype files: list[str]
"""
_validation = {
'files': {'required': True},
}
_attribute_map = {
'format': {'key': 'format', 'type': 'str'},
'files': {'key': 'files', 'type': '[str]'},
}
def __init__(
self,
*,
files: List[str],
format: Optional[str] = None,
**kwargs
):
"""
:keyword format: File format.
:paramtype format: str
:keyword files: Required. files to import.
:paramtype files: list[str]
"""
super(ImportRDBParameters, self).__init__(**kwargs)
self.format = format
self.files = files
class ManagedServiceIdentity(msrest.serialization.Model):
"""Managed service identity (system assigned and/or user assigned identities).
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar principal_id: The service principal ID of the system assigned identity. This property
will only be provided for a system assigned identity.
:vartype principal_id: str
:ivar tenant_id: The tenant ID of the system assigned identity. This property will only be
provided for a system assigned identity.
:vartype tenant_id: str
:ivar type: Required. Type of managed service identity (where both SystemAssigned and
UserAssigned types are allowed). Possible values include: "None", "SystemAssigned",
"UserAssigned", "SystemAssigned, UserAssigned".
:vartype type: str or ~azure.mgmt.redis.models.ManagedServiceIdentityType
:ivar user_assigned_identities: The set of user assigned identities associated with the
resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form:
'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}.
The dictionary values can be empty objects ({}) in requests.
:vartype user_assigned_identities: dict[str, ~azure.mgmt.redis.models.UserAssignedIdentity]
"""
_validation = {
'principal_id': {'readonly': True},
'tenant_id': {'readonly': True},
'type': {'required': True},
}
_attribute_map = {
'principal_id': {'key': 'principalId', 'type': 'str'},
'tenant_id': {'key': 'tenantId', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'user_assigned_identities': {'key': 'userAssignedIdentities', 'type': '{UserAssignedIdentity}'},
}
def __init__(
self,
*,
type: Union[str, "ManagedServiceIdentityType"],
user_assigned_identities: Optional[Dict[str, "UserAssignedIdentity"]] = None,
**kwargs
):
"""
:keyword type: Required. Type of managed service identity (where both SystemAssigned and
UserAssigned types are allowed). Possible values include: "None", "SystemAssigned",
"UserAssigned", "SystemAssigned, UserAssigned".
:paramtype type: str or ~azure.mgmt.redis.models.ManagedServiceIdentityType
:keyword user_assigned_identities: The set of user assigned identities associated with the
resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form:
'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}.
The dictionary values can be empty objects ({}) in requests.
:paramtype user_assigned_identities: dict[str, ~azure.mgmt.redis.models.UserAssignedIdentity]
"""
super(ManagedServiceIdentity, self).__init__(**kwargs)
self.principal_id = None
self.tenant_id = None
self.type = type
self.user_assigned_identities = user_assigned_identities
class NotificationListResponse(msrest.serialization.Model):
"""The response of listUpgradeNotifications.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: List of all notifications.
:vartype value: list[~azure.mgmt.redis.models.UpgradeNotification]
:ivar next_link: Link for next set of notifications.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[UpgradeNotification]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["UpgradeNotification"]] = None,
**kwargs
):
"""
:keyword value: List of all notifications.
:paramtype value: list[~azure.mgmt.redis.models.UpgradeNotification]
"""
super(NotificationListResponse, self).__init__(**kwargs)
self.value = value
self.next_link = None
class Operation(msrest.serialization.Model):
"""REST API operation.
:ivar name: Operation name: {provider}/{resource}/{operation}.
:vartype name: str
:ivar display: The object that describes the operation.
:vartype display: ~azure.mgmt.redis.models.OperationDisplay
"""
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'display': {'key': 'display', 'type': 'OperationDisplay'},
}
def __init__(
self,
*,
name: Optional[str] = None,
display: Optional["OperationDisplay"] = None,
**kwargs
):
"""
:keyword name: Operation name: {provider}/{resource}/{operation}.
:paramtype name: str
:keyword display: The object that describes the operation.
:paramtype display: ~azure.mgmt.redis.models.OperationDisplay
"""
super(Operation, self).__init__(**kwargs)
self.name = name
self.display = display
class OperationDisplay(msrest.serialization.Model):
"""The object that describes the operation.
:ivar provider: Friendly name of the resource provider.
:vartype provider: str
:ivar operation: Operation type: read, write, delete, listKeys/action, etc.
:vartype operation: str
:ivar resource: Resource type on which the operation is performed.
:vartype resource: str
:ivar description: Friendly name of the operation.
:vartype description: str
"""
_attribute_map = {
'provider': {'key': 'provider', 'type': 'str'},
'operation': {'key': 'operation', 'type': 'str'},
'resource': {'key': 'resource', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
}
def __init__(
self,
*,
provider: Optional[str] = None,
operation: Optional[str] = None,
resource: Optional[str] = None,
description: Optional[str] = None,
**kwargs
):
"""
:keyword provider: Friendly name of the resource provider.
:paramtype provider: str
:keyword operation: Operation type: read, write, delete, listKeys/action, etc.
:paramtype operation: str
:keyword resource: Resource type on which the operation is performed.
:paramtype resource: str
:keyword description: Friendly name of the operation.
:paramtype description: str
"""
super(OperationDisplay, self).__init__(**kwargs)
self.provider = provider
self.operation = operation
self.resource = resource
self.description = description
class OperationListResult(msrest.serialization.Model):
"""Result of the request to list REST API operations. It contains a list of operations and a URL nextLink to get the next set of results.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: List of operations supported by the resource provider.
:vartype value: list[~azure.mgmt.redis.models.Operation]
:ivar next_link: URL to get the next set of operation list results if there are any.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[Operation]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["Operation"]] = None,
**kwargs
):
"""
:keyword value: List of operations supported by the resource provider.
:paramtype value: list[~azure.mgmt.redis.models.Operation]
"""
super(OperationListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class PrivateEndpoint(msrest.serialization.Model):
"""The Private Endpoint resource.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: The ARM identifier for Private Endpoint.
:vartype id: str
"""
_validation = {
'id': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(PrivateEndpoint, self).__init__(**kwargs)
self.id = None
class Resource(msrest.serialization.Model):
"""Common fields that are returned in the response for all Azure Resource Manager resources.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(Resource, self).__init__(**kwargs)
self.id = None
self.name = None
self.type = None
class PrivateEndpointConnection(Resource):
"""The Private Endpoint Connection resource.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar private_endpoint: The resource of private end point.
:vartype private_endpoint: ~azure.mgmt.redis.models.PrivateEndpoint
:ivar private_link_service_connection_state: A collection of information about the state of the
connection between service consumer and provider.
:vartype private_link_service_connection_state:
~azure.mgmt.redis.models.PrivateLinkServiceConnectionState
:ivar provisioning_state: The provisioning state of the private endpoint connection resource.
Possible values include: "Succeeded", "Creating", "Deleting", "Failed".
:vartype provisioning_state: str or
~azure.mgmt.redis.models.PrivateEndpointConnectionProvisioningState
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'provisioning_state': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'private_endpoint': {'key': 'properties.privateEndpoint', 'type': 'PrivateEndpoint'},
'private_link_service_connection_state': {'key': 'properties.privateLinkServiceConnectionState', 'type': 'PrivateLinkServiceConnectionState'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
}
def __init__(
self,
*,
private_endpoint: Optional["PrivateEndpoint"] = None,
private_link_service_connection_state: Optional["PrivateLinkServiceConnectionState"] = None,
**kwargs
):
"""
:keyword private_endpoint: The resource of private end point.
:paramtype private_endpoint: ~azure.mgmt.redis.models.PrivateEndpoint
:keyword private_link_service_connection_state: A collection of information about the state of
the connection between service consumer and provider.
:paramtype private_link_service_connection_state:
~azure.mgmt.redis.models.PrivateLinkServiceConnectionState
"""
super(PrivateEndpointConnection, self).__init__(**kwargs)
self.private_endpoint = private_endpoint
self.private_link_service_connection_state = private_link_service_connection_state
self.provisioning_state = None
class PrivateEndpointConnectionListResult(msrest.serialization.Model):
"""List of private endpoint connection associated with the specified storage account.
:ivar value: Array of private endpoint connections.
:vartype value: list[~azure.mgmt.redis.models.PrivateEndpointConnection]
"""
_attribute_map = {
'value': {'key': 'value', 'type': '[PrivateEndpointConnection]'},
}
def __init__(
self,
*,
value: Optional[List["PrivateEndpointConnection"]] = None,
**kwargs
):
"""
:keyword value: Array of private endpoint connections.
:paramtype value: list[~azure.mgmt.redis.models.PrivateEndpointConnection]
"""
super(PrivateEndpointConnectionListResult, self).__init__(**kwargs)
self.value = value
class PrivateLinkResource(Resource):
"""A private link resource.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar group_id: The private link resource group id.
:vartype group_id: str
:ivar required_members: The private link resource required member names.
:vartype required_members: list[str]
:ivar required_zone_names: The private link resource Private link DNS zone name.
:vartype required_zone_names: list[str]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'group_id': {'readonly': True},
'required_members': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'group_id': {'key': 'properties.groupId', 'type': 'str'},
'required_members': {'key': 'properties.requiredMembers', 'type': '[str]'},
'required_zone_names': {'key': 'properties.requiredZoneNames', 'type': '[str]'},
}
def __init__(
self,
*,
required_zone_names: Optional[List[str]] = None,
**kwargs
):
"""
:keyword required_zone_names: The private link resource Private link DNS zone name.
:paramtype required_zone_names: list[str]
"""
super(PrivateLinkResource, self).__init__(**kwargs)
self.group_id = None
self.required_members = None
self.required_zone_names = required_zone_names
class PrivateLinkResourceListResult(msrest.serialization.Model):
"""A list of private link resources.
:ivar value: Array of private link resources.
:vartype value: list[~azure.mgmt.redis.models.PrivateLinkResource]
"""
_attribute_map = {
'value': {'key': 'value', 'type': '[PrivateLinkResource]'},
}
def __init__(
self,
*,
value: Optional[List["PrivateLinkResource"]] = None,
**kwargs
):
"""
:keyword value: Array of private link resources.
:paramtype value: list[~azure.mgmt.redis.models.PrivateLinkResource]
"""
super(PrivateLinkResourceListResult, self).__init__(**kwargs)
self.value = value
class PrivateLinkServiceConnectionState(msrest.serialization.Model):
"""A collection of information about the state of the connection between service consumer and provider.
:ivar status: Indicates whether the connection has been Approved/Rejected/Removed by the owner
of the service. Possible values include: "Pending", "Approved", "Rejected".
:vartype status: str or ~azure.mgmt.redis.models.PrivateEndpointServiceConnectionStatus
:ivar description: The reason for approval/rejection of the connection.
:vartype description: str
:ivar actions_required: A message indicating if changes on the service provider require any
updates on the consumer.
:vartype actions_required: str
"""
_attribute_map = {
'status': {'key': 'status', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
'actions_required': {'key': 'actionsRequired', 'type': 'str'},
}
def __init__(
self,
*,
status: Optional[Union[str, "PrivateEndpointServiceConnectionStatus"]] = None,
description: Optional[str] = None,
actions_required: Optional[str] = None,
**kwargs
):
"""
:keyword status: Indicates whether the connection has been Approved/Rejected/Removed by the
owner of the service. Possible values include: "Pending", "Approved", "Rejected".
:paramtype status: str or ~azure.mgmt.redis.models.PrivateEndpointServiceConnectionStatus
:keyword description: The reason for approval/rejection of the connection.
:paramtype description: str
:keyword actions_required: A message indicating if changes on the service provider require any
updates on the consumer.
:paramtype actions_required: str
"""
super(PrivateLinkServiceConnectionState, self).__init__(**kwargs)
self.status = status
self.description = description
self.actions_required = actions_required
class ProxyResource(Resource):
"""The resource model definition for a Azure Resource Manager proxy resource. It will not have tags and a location.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(ProxyResource, self).__init__(**kwargs)
class RedisAccessKeys(msrest.serialization.Model):
"""Redis cache access keys.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar primary_key: The current primary key that clients can use to authenticate with Redis
cache.
:vartype primary_key: str
:ivar secondary_key: The current secondary key that clients can use to authenticate with Redis
cache.
:vartype secondary_key: str
"""
_validation = {
'primary_key': {'readonly': True},
'secondary_key': {'readonly': True},
}
_attribute_map = {
'primary_key': {'key': 'primaryKey', 'type': 'str'},
'secondary_key': {'key': 'secondaryKey', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(RedisAccessKeys, self).__init__(**kwargs)
self.primary_key = None
self.secondary_key = None
class RedisCommonProperties(msrest.serialization.Model):
"""Create/Update/Get common properties of the redis cache.
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
"""
_attribute_map = {
'redis_configuration': {'key': 'redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'publicNetworkAccess', 'type': 'str'},
}
def __init__(
self,
*,
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
**kwargs
):
"""
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
"""
super(RedisCommonProperties, self).__init__(**kwargs)
self.redis_configuration = redis_configuration
self.redis_version = redis_version
self.enable_non_ssl_port = enable_non_ssl_port
self.replicas_per_master = replicas_per_master
self.replicas_per_primary = replicas_per_primary
self.tenant_settings = tenant_settings
self.shard_count = shard_count
self.minimum_tls_version = minimum_tls_version
self.public_network_access = public_network_access
class RedisCommonPropertiesRedisConfiguration(msrest.serialization.Model):
"""All Redis Settings. Few possible keys: rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value etc.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar additional_properties: Unmatched properties from the message are deserialized to this
collection.
:vartype additional_properties: dict[str, any]
:ivar rdb_backup_enabled: Specifies whether the rdb backup is enabled.
:vartype rdb_backup_enabled: str
:ivar rdb_backup_frequency: Specifies the frequency for creating rdb backup.
:vartype rdb_backup_frequency: str
:ivar rdb_backup_max_snapshot_count: Specifies the maximum number of snapshots for rdb backup.
:vartype rdb_backup_max_snapshot_count: str
:ivar rdb_storage_connection_string: The storage account connection string for storing rdb
file.
:vartype rdb_storage_connection_string: str
:ivar aof_storage_connection_string0: First storage account connection string.
:vartype aof_storage_connection_string0: str
:ivar aof_storage_connection_string1: Second storage account connection string.
:vartype aof_storage_connection_string1: str
:ivar maxfragmentationmemory_reserved: Value in megabytes reserved for fragmentation per shard.
:vartype maxfragmentationmemory_reserved: str
:ivar maxmemory_policy: The eviction strategy used when your data won't fit within its memory
limit.
:vartype maxmemory_policy: str
:ivar maxmemory_reserved: Value in megabytes reserved for non-cache usage per shard e.g.
failover.
:vartype maxmemory_reserved: str
:ivar maxmemory_delta: Value in megabytes reserved for non-cache usage per shard e.g. failover.
:vartype maxmemory_delta: str
:ivar maxclients: The max clients config.
:vartype maxclients: str
:ivar preferred_data_archive_auth_method: Preferred auth method to communicate to storage
account used for data archive, specify SAS or ManagedIdentity, default value is SAS.
:vartype preferred_data_archive_auth_method: str
:ivar preferred_data_persistence_auth_method: Preferred auth method to communicate to storage
account used for data persistence, specify SAS or ManagedIdentity, default value is SAS.
:vartype preferred_data_persistence_auth_method: str
"""
_validation = {
'maxclients': {'readonly': True},
'preferred_data_archive_auth_method': {'readonly': True},
'preferred_data_persistence_auth_method': {'readonly': True},
}
_attribute_map = {
'additional_properties': {'key': '', 'type': '{object}'},
'rdb_backup_enabled': {'key': 'rdb-backup-enabled', 'type': 'str'},
'rdb_backup_frequency': {'key': 'rdb-backup-frequency', 'type': 'str'},
'rdb_backup_max_snapshot_count': {'key': 'rdb-backup-max-snapshot-count', 'type': 'str'},
'rdb_storage_connection_string': {'key': 'rdb-storage-connection-string', 'type': 'str'},
'aof_storage_connection_string0': {'key': 'aof-storage-connection-string-0', 'type': 'str'},
'aof_storage_connection_string1': {'key': 'aof-storage-connection-string-1', 'type': 'str'},
'maxfragmentationmemory_reserved': {'key': 'maxfragmentationmemory-reserved', 'type': 'str'},
'maxmemory_policy': {'key': 'maxmemory-policy', 'type': 'str'},
'maxmemory_reserved': {'key': 'maxmemory-reserved', 'type': 'str'},
'maxmemory_delta': {'key': 'maxmemory-delta', 'type': 'str'},
'maxclients': {'key': 'maxclients', 'type': 'str'},
'preferred_data_archive_auth_method': {'key': 'preferred-data-archive-auth-method', 'type': 'str'},
'preferred_data_persistence_auth_method': {'key': 'preferred-data-persistence-auth-method', 'type': 'str'},
}
def __init__(
self,
*,
additional_properties: Optional[Dict[str, Any]] = None,
rdb_backup_enabled: Optional[str] = None,
rdb_backup_frequency: Optional[str] = None,
rdb_backup_max_snapshot_count: Optional[str] = None,
rdb_storage_connection_string: Optional[str] = None,
aof_storage_connection_string0: Optional[str] = None,
aof_storage_connection_string1: Optional[str] = None,
maxfragmentationmemory_reserved: Optional[str] = None,
maxmemory_policy: Optional[str] = None,
maxmemory_reserved: Optional[str] = None,
maxmemory_delta: Optional[str] = None,
**kwargs
):
"""
:keyword additional_properties: Unmatched properties from the message are deserialized to this
collection.
:paramtype additional_properties: dict[str, any]
:keyword rdb_backup_enabled: Specifies whether the rdb backup is enabled.
:paramtype rdb_backup_enabled: str
:keyword rdb_backup_frequency: Specifies the frequency for creating rdb backup.
:paramtype rdb_backup_frequency: str
:keyword rdb_backup_max_snapshot_count: Specifies the maximum number of snapshots for rdb
backup.
:paramtype rdb_backup_max_snapshot_count: str
:keyword rdb_storage_connection_string: The storage account connection string for storing rdb
file.
:paramtype rdb_storage_connection_string: str
:keyword aof_storage_connection_string0: First storage account connection string.
:paramtype aof_storage_connection_string0: str
:keyword aof_storage_connection_string1: Second storage account connection string.
:paramtype aof_storage_connection_string1: str
:keyword maxfragmentationmemory_reserved: Value in megabytes reserved for fragmentation per
shard.
:paramtype maxfragmentationmemory_reserved: str
:keyword maxmemory_policy: The eviction strategy used when your data won't fit within its
memory limit.
:paramtype maxmemory_policy: str
:keyword maxmemory_reserved: Value in megabytes reserved for non-cache usage per shard e.g.
failover.
:paramtype maxmemory_reserved: str
:keyword maxmemory_delta: Value in megabytes reserved for non-cache usage per shard e.g.
failover.
:paramtype maxmemory_delta: str
"""
super(RedisCommonPropertiesRedisConfiguration, self).__init__(**kwargs)
self.additional_properties = additional_properties
self.rdb_backup_enabled = rdb_backup_enabled
self.rdb_backup_frequency = rdb_backup_frequency
self.rdb_backup_max_snapshot_count = rdb_backup_max_snapshot_count
self.rdb_storage_connection_string = rdb_storage_connection_string
self.aof_storage_connection_string0 = aof_storage_connection_string0
self.aof_storage_connection_string1 = aof_storage_connection_string1
self.maxfragmentationmemory_reserved = maxfragmentationmemory_reserved
self.maxmemory_policy = maxmemory_policy
self.maxmemory_reserved = maxmemory_reserved
self.maxmemory_delta = maxmemory_delta
self.maxclients = None
self.preferred_data_archive_auth_method = None
self.preferred_data_persistence_auth_method = None
class RedisCreateParameters(msrest.serialization.Model):
"""Parameters supplied to the Create Redis operation.
All required parameters must be populated in order to send to Azure.
:ivar zones: A list of availability zones denoting where the resource needs to come from.
:vartype zones: list[str]
:ivar location: Required. The geo-location where the resource lives.
:vartype location: str
:ivar tags: A set of tags. Resource tags.
:vartype tags: dict[str, str]
:ivar identity: The identity of the resource.
:vartype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: Required. The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
:ivar subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:vartype subnet_id: str
:ivar static_ip: Static IP address. Optionally, may be specified when deploying a Redis cache
inside an existing Azure Virtual Network; auto assigned by default.
:vartype static_ip: str
"""
_validation = {
'location': {'required': True},
'sku': {'required': True},
'subnet_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'},
'static_ip': {'pattern': r'^\d+\.\d+\.\d+\.\d+$'},
}
_attribute_map = {
'zones': {'key': 'zones', 'type': '[str]'},
'location': {'key': 'location', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'identity': {'key': 'identity', 'type': 'ManagedServiceIdentity'},
'redis_configuration': {'key': 'properties.redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'properties.redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'properties.enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'properties.replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'properties.replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'properties.tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'properties.shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'properties.minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'properties.publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'properties.sku', 'type': 'Sku'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'static_ip': {'key': 'properties.staticIP', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
sku: "Sku",
zones: Optional[List[str]] = None,
tags: Optional[Dict[str, str]] = None,
identity: Optional["ManagedServiceIdentity"] = None,
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
subnet_id: Optional[str] = None,
static_ip: Optional[str] = None,
**kwargs
):
"""
:keyword zones: A list of availability zones denoting where the resource needs to come from.
:paramtype zones: list[str]
:keyword location: Required. The geo-location where the resource lives.
:paramtype location: str
:keyword tags: A set of tags. Resource tags.
:paramtype tags: dict[str, str]
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: Required. The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
:keyword subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:paramtype subnet_id: str
:keyword static_ip: Static IP address. Optionally, may be specified when deploying a Redis
cache inside an existing Azure Virtual Network; auto assigned by default.
:paramtype static_ip: str
"""
super(RedisCreateParameters, self).__init__(**kwargs)
self.zones = zones
self.location = location
self.tags = tags
self.identity = identity
self.redis_configuration = redis_configuration
self.redis_version = redis_version
self.enable_non_ssl_port = enable_non_ssl_port
self.replicas_per_master = replicas_per_master
self.replicas_per_primary = replicas_per_primary
self.tenant_settings = tenant_settings
self.shard_count = shard_count
self.minimum_tls_version = minimum_tls_version
self.public_network_access = public_network_access
self.sku = sku
self.subnet_id = subnet_id
self.static_ip = static_ip
class RedisCreateProperties(RedisCommonProperties):
"""Properties supplied to Create Redis operation.
All required parameters must be populated in order to send to Azure.
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: Required. The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
:ivar subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:vartype subnet_id: str
:ivar static_ip: Static IP address. Optionally, may be specified when deploying a Redis cache
inside an existing Azure Virtual Network; auto assigned by default.
:vartype static_ip: str
"""
_validation = {
'sku': {'required': True},
'subnet_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'},
'static_ip': {'pattern': r'^\d+\.\d+\.\d+\.\d+$'},
}
_attribute_map = {
'redis_configuration': {'key': 'redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'sku', 'type': 'Sku'},
'subnet_id': {'key': 'subnetId', 'type': 'str'},
'static_ip': {'key': 'staticIP', 'type': 'str'},
}
def __init__(
self,
*,
sku: "Sku",
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
subnet_id: Optional[str] = None,
static_ip: Optional[str] = None,
**kwargs
):
"""
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: Required. The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
:keyword subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:paramtype subnet_id: str
:keyword static_ip: Static IP address. Optionally, may be specified when deploying a Redis
cache inside an existing Azure Virtual Network; auto assigned by default.
:paramtype static_ip: str
"""
super(RedisCreateProperties, self).__init__(redis_configuration=redis_configuration, redis_version=redis_version, enable_non_ssl_port=enable_non_ssl_port, replicas_per_master=replicas_per_master, replicas_per_primary=replicas_per_primary, tenant_settings=tenant_settings, shard_count=shard_count, minimum_tls_version=minimum_tls_version, public_network_access=public_network_access, **kwargs)
self.sku = sku
self.subnet_id = subnet_id
self.static_ip = static_ip
class RedisFirewallRule(ProxyResource):
"""A firewall rule on a redis cache has a name, and describes a contiguous range of IP addresses permitted to connect.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar start_ip: Required. lowest IP address included in the range.
:vartype start_ip: str
:ivar end_ip: Required. highest IP address included in the range.
:vartype end_ip: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'start_ip': {'required': True},
'end_ip': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'start_ip': {'key': 'properties.startIP', 'type': 'str'},
'end_ip': {'key': 'properties.endIP', 'type': 'str'},
}
def __init__(
self,
*,
start_ip: str,
end_ip: str,
**kwargs
):
"""
:keyword start_ip: Required. lowest IP address included in the range.
:paramtype start_ip: str
:keyword end_ip: Required. highest IP address included in the range.
:paramtype end_ip: str
"""
super(RedisFirewallRule, self).__init__(**kwargs)
self.start_ip = start_ip
self.end_ip = end_ip
class RedisFirewallRuleCreateParameters(RedisFirewallRule):
"""Parameters required for creating a firewall rule on redis cache. (Note, you can just use the FirewallRule type instead now.).
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar start_ip: Required. lowest IP address included in the range.
:vartype start_ip: str
:ivar end_ip: Required. highest IP address included in the range.
:vartype end_ip: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'start_ip': {'required': True},
'end_ip': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'start_ip': {'key': 'properties.startIP', 'type': 'str'},
'end_ip': {'key': 'properties.endIP', 'type': 'str'},
}
def __init__(
self,
*,
start_ip: str,
end_ip: str,
**kwargs
):
"""
:keyword start_ip: Required. lowest IP address included in the range.
:paramtype start_ip: str
:keyword end_ip: Required. highest IP address included in the range.
:paramtype end_ip: str
"""
super(RedisFirewallRuleCreateParameters, self).__init__(start_ip=start_ip, end_ip=end_ip, **kwargs)
class RedisFirewallRuleListResult(msrest.serialization.Model):
"""The response of list firewall rules Redis operation.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: Results of the list firewall rules operation.
:vartype value: list[~azure.mgmt.redis.models.RedisFirewallRule]
:ivar next_link: Link for next page of results.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[RedisFirewallRule]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["RedisFirewallRule"]] = None,
**kwargs
):
"""
:keyword value: Results of the list firewall rules operation.
:paramtype value: list[~azure.mgmt.redis.models.RedisFirewallRule]
"""
super(RedisFirewallRuleListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class RedisForceRebootResponse(msrest.serialization.Model):
"""Response to force reboot for Redis cache.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar message: Status message.
:vartype message: str
"""
_validation = {
'message': {'readonly': True},
}
_attribute_map = {
'message': {'key': 'message', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(RedisForceRebootResponse, self).__init__(**kwargs)
self.message = None
class RedisInstanceDetails(msrest.serialization.Model):
"""Details of single instance of redis.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar ssl_port: Redis instance SSL port.
:vartype ssl_port: int
:ivar non_ssl_port: If enableNonSslPort is true, provides Redis instance Non-SSL port.
:vartype non_ssl_port: int
:ivar zone: If the Cache uses availability zones, specifies availability zone where this
instance is located.
:vartype zone: str
:ivar shard_id: If clustering is enabled, the Shard ID of Redis Instance.
:vartype shard_id: int
:ivar is_master: Specifies whether the instance is a primary node.
:vartype is_master: bool
:ivar is_primary: Specifies whether the instance is a primary node.
:vartype is_primary: bool
"""
_validation = {
'ssl_port': {'readonly': True},
'non_ssl_port': {'readonly': True},
'zone': {'readonly': True},
'shard_id': {'readonly': True},
'is_master': {'readonly': True},
'is_primary': {'readonly': True},
}
_attribute_map = {
'ssl_port': {'key': 'sslPort', 'type': 'int'},
'non_ssl_port': {'key': 'nonSslPort', 'type': 'int'},
'zone': {'key': 'zone', 'type': 'str'},
'shard_id': {'key': 'shardId', 'type': 'int'},
'is_master': {'key': 'isMaster', 'type': 'bool'},
'is_primary': {'key': 'isPrimary', 'type': 'bool'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(RedisInstanceDetails, self).__init__(**kwargs)
self.ssl_port = None
self.non_ssl_port = None
self.zone = None
self.shard_id = None
self.is_master = None
self.is_primary = None
class RedisLinkedServer(msrest.serialization.Model):
"""Linked server Id.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Linked server Id.
:vartype id: str
"""
_validation = {
'id': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(RedisLinkedServer, self).__init__(**kwargs)
self.id = None
class RedisLinkedServerCreateParameters(msrest.serialization.Model):
"""Parameter required for creating a linked server to redis cache.
All required parameters must be populated in order to send to Azure.
:ivar linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:vartype linked_redis_cache_id: str
:ivar linked_redis_cache_location: Required. Location of the linked redis cache.
:vartype linked_redis_cache_location: str
:ivar server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:vartype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
_validation = {
'linked_redis_cache_id': {'required': True},
'linked_redis_cache_location': {'required': True},
'server_role': {'required': True},
}
_attribute_map = {
'linked_redis_cache_id': {'key': 'properties.linkedRedisCacheId', 'type': 'str'},
'linked_redis_cache_location': {'key': 'properties.linkedRedisCacheLocation', 'type': 'str'},
'server_role': {'key': 'properties.serverRole', 'type': 'str'},
}
def __init__(
self,
*,
linked_redis_cache_id: str,
linked_redis_cache_location: str,
server_role: Union[str, "ReplicationRole"],
**kwargs
):
"""
:keyword linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:paramtype linked_redis_cache_id: str
:keyword linked_redis_cache_location: Required. Location of the linked redis cache.
:paramtype linked_redis_cache_location: str
:keyword server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:paramtype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
super(RedisLinkedServerCreateParameters, self).__init__(**kwargs)
self.linked_redis_cache_id = linked_redis_cache_id
self.linked_redis_cache_location = linked_redis_cache_location
self.server_role = server_role
class RedisLinkedServerCreateProperties(msrest.serialization.Model):
"""Create properties for a linked server.
All required parameters must be populated in order to send to Azure.
:ivar linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:vartype linked_redis_cache_id: str
:ivar linked_redis_cache_location: Required. Location of the linked redis cache.
:vartype linked_redis_cache_location: str
:ivar server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:vartype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
_validation = {
'linked_redis_cache_id': {'required': True},
'linked_redis_cache_location': {'required': True},
'server_role': {'required': True},
}
_attribute_map = {
'linked_redis_cache_id': {'key': 'linkedRedisCacheId', 'type': 'str'},
'linked_redis_cache_location': {'key': 'linkedRedisCacheLocation', 'type': 'str'},
'server_role': {'key': 'serverRole', 'type': 'str'},
}
def __init__(
self,
*,
linked_redis_cache_id: str,
linked_redis_cache_location: str,
server_role: Union[str, "ReplicationRole"],
**kwargs
):
"""
:keyword linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:paramtype linked_redis_cache_id: str
:keyword linked_redis_cache_location: Required. Location of the linked redis cache.
:paramtype linked_redis_cache_location: str
:keyword server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:paramtype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
super(RedisLinkedServerCreateProperties, self).__init__(**kwargs)
self.linked_redis_cache_id = linked_redis_cache_id
self.linked_redis_cache_location = linked_redis_cache_location
self.server_role = server_role
class RedisLinkedServerProperties(RedisLinkedServerCreateProperties):
"""Properties of a linked server to be returned in get/put response.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:vartype linked_redis_cache_id: str
:ivar linked_redis_cache_location: Required. Location of the linked redis cache.
:vartype linked_redis_cache_location: str
:ivar server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:vartype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
:ivar provisioning_state: Terminal state of the link between primary and secondary redis cache.
:vartype provisioning_state: str
"""
_validation = {
'linked_redis_cache_id': {'required': True},
'linked_redis_cache_location': {'required': True},
'server_role': {'required': True},
'provisioning_state': {'readonly': True},
}
_attribute_map = {
'linked_redis_cache_id': {'key': 'linkedRedisCacheId', 'type': 'str'},
'linked_redis_cache_location': {'key': 'linkedRedisCacheLocation', 'type': 'str'},
'server_role': {'key': 'serverRole', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
}
def __init__(
self,
*,
linked_redis_cache_id: str,
linked_redis_cache_location: str,
server_role: Union[str, "ReplicationRole"],
**kwargs
):
"""
:keyword linked_redis_cache_id: Required. Fully qualified resourceId of the linked redis cache.
:paramtype linked_redis_cache_id: str
:keyword linked_redis_cache_location: Required. Location of the linked redis cache.
:paramtype linked_redis_cache_location: str
:keyword server_role: Required. Role of the linked server. Possible values include: "Primary",
"Secondary".
:paramtype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
super(RedisLinkedServerProperties, self).__init__(linked_redis_cache_id=linked_redis_cache_id, linked_redis_cache_location=linked_redis_cache_location, server_role=server_role, **kwargs)
self.provisioning_state = None
class RedisLinkedServerWithProperties(ProxyResource):
"""Response to put/get linked server (with properties) for Redis cache.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar linked_redis_cache_id: Fully qualified resourceId of the linked redis cache.
:vartype linked_redis_cache_id: str
:ivar linked_redis_cache_location: Location of the linked redis cache.
:vartype linked_redis_cache_location: str
:ivar server_role: Role of the linked server. Possible values include: "Primary", "Secondary".
:vartype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
:ivar provisioning_state: Terminal state of the link between primary and secondary redis cache.
:vartype provisioning_state: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'provisioning_state': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'linked_redis_cache_id': {'key': 'properties.linkedRedisCacheId', 'type': 'str'},
'linked_redis_cache_location': {'key': 'properties.linkedRedisCacheLocation', 'type': 'str'},
'server_role': {'key': 'properties.serverRole', 'type': 'str'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
}
def __init__(
self,
*,
linked_redis_cache_id: Optional[str] = None,
linked_redis_cache_location: Optional[str] = None,
server_role: Optional[Union[str, "ReplicationRole"]] = None,
**kwargs
):
"""
:keyword linked_redis_cache_id: Fully qualified resourceId of the linked redis cache.
:paramtype linked_redis_cache_id: str
:keyword linked_redis_cache_location: Location of the linked redis cache.
:paramtype linked_redis_cache_location: str
:keyword server_role: Role of the linked server. Possible values include: "Primary",
"Secondary".
:paramtype server_role: str or ~azure.mgmt.redis.models.ReplicationRole
"""
super(RedisLinkedServerWithProperties, self).__init__(**kwargs)
self.linked_redis_cache_id = linked_redis_cache_id
self.linked_redis_cache_location = linked_redis_cache_location
self.server_role = server_role
self.provisioning_state = None
class RedisLinkedServerWithPropertiesList(msrest.serialization.Model):
"""List of linked servers (with properties) of a Redis cache.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: List of linked servers (with properties) of a Redis cache.
:vartype value: list[~azure.mgmt.redis.models.RedisLinkedServerWithProperties]
:ivar next_link: Link for next set.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[RedisLinkedServerWithProperties]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["RedisLinkedServerWithProperties"]] = None,
**kwargs
):
"""
:keyword value: List of linked servers (with properties) of a Redis cache.
:paramtype value: list[~azure.mgmt.redis.models.RedisLinkedServerWithProperties]
"""
super(RedisLinkedServerWithPropertiesList, self).__init__(**kwargs)
self.value = value
self.next_link = None
class RedisListResult(msrest.serialization.Model):
"""The response of list Redis operation.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: List of Redis cache instances.
:vartype value: list[~azure.mgmt.redis.models.RedisResource]
:ivar next_link: Link for next page of results.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[RedisResource]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["RedisResource"]] = None,
**kwargs
):
"""
:keyword value: List of Redis cache instances.
:paramtype value: list[~azure.mgmt.redis.models.RedisResource]
"""
super(RedisListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class RedisPatchSchedule(ProxyResource):
"""Response to put/get patch schedules for Redis cache.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar schedule_entries: Required. List of patch schedules for a Redis cache.
:vartype schedule_entries: list[~azure.mgmt.redis.models.ScheduleEntry]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'schedule_entries': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'schedule_entries': {'key': 'properties.scheduleEntries', 'type': '[ScheduleEntry]'},
}
def __init__(
self,
*,
schedule_entries: List["ScheduleEntry"],
**kwargs
):
"""
:keyword schedule_entries: Required. List of patch schedules for a Redis cache.
:paramtype schedule_entries: list[~azure.mgmt.redis.models.ScheduleEntry]
"""
super(RedisPatchSchedule, self).__init__(**kwargs)
self.schedule_entries = schedule_entries
class RedisPatchScheduleListResult(msrest.serialization.Model):
"""The response of list patch schedules Redis operation.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar value: Results of the list patch schedules operation.
:vartype value: list[~azure.mgmt.redis.models.RedisPatchSchedule]
:ivar next_link: Link for next page of results.
:vartype next_link: str
"""
_validation = {
'next_link': {'readonly': True},
}
_attribute_map = {
'value': {'key': 'value', 'type': '[RedisPatchSchedule]'},
'next_link': {'key': 'nextLink', 'type': 'str'},
}
def __init__(
self,
*,
value: Optional[List["RedisPatchSchedule"]] = None,
**kwargs
):
"""
:keyword value: Results of the list patch schedules operation.
:paramtype value: list[~azure.mgmt.redis.models.RedisPatchSchedule]
"""
super(RedisPatchScheduleListResult, self).__init__(**kwargs)
self.value = value
self.next_link = None
class RedisProperties(RedisCreateProperties):
"""Properties of the redis cache.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: Required. The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
:ivar subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:vartype subnet_id: str
:ivar static_ip: Static IP address. Optionally, may be specified when deploying a Redis cache
inside an existing Azure Virtual Network; auto assigned by default.
:vartype static_ip: str
:ivar provisioning_state: Redis instance provisioning status. Possible values include:
"Creating", "Deleting", "Disabled", "Failed", "Linking", "Provisioning",
"RecoveringScaleFailure", "Scaling", "Succeeded", "Unlinking", "Unprovisioning", "Updating".
:vartype provisioning_state: str or ~azure.mgmt.redis.models.ProvisioningState
:ivar host_name: Redis host name.
:vartype host_name: str
:ivar port: Redis non-SSL port.
:vartype port: int
:ivar ssl_port: Redis SSL port.
:vartype ssl_port: int
:ivar access_keys: The keys of the Redis cache - not set if this object is not the response to
Create or Update redis cache.
:vartype access_keys: ~azure.mgmt.redis.models.RedisAccessKeys
:ivar linked_servers: List of the linked servers associated with the cache.
:vartype linked_servers: list[~azure.mgmt.redis.models.RedisLinkedServer]
:ivar instances: List of the Redis instances associated with the cache.
:vartype instances: list[~azure.mgmt.redis.models.RedisInstanceDetails]
:ivar private_endpoint_connections: List of private endpoint connection associated with the
specified redis cache.
:vartype private_endpoint_connections: list[~azure.mgmt.redis.models.PrivateEndpointConnection]
"""
_validation = {
'sku': {'required': True},
'subnet_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'},
'static_ip': {'pattern': r'^\d+\.\d+\.\d+\.\d+$'},
'provisioning_state': {'readonly': True},
'host_name': {'readonly': True},
'port': {'readonly': True},
'ssl_port': {'readonly': True},
'access_keys': {'readonly': True},
'linked_servers': {'readonly': True},
'instances': {'readonly': True},
'private_endpoint_connections': {'readonly': True},
}
_attribute_map = {
'redis_configuration': {'key': 'redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'sku', 'type': 'Sku'},
'subnet_id': {'key': 'subnetId', 'type': 'str'},
'static_ip': {'key': 'staticIP', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
'host_name': {'key': 'hostName', 'type': 'str'},
'port': {'key': 'port', 'type': 'int'},
'ssl_port': {'key': 'sslPort', 'type': 'int'},
'access_keys': {'key': 'accessKeys', 'type': 'RedisAccessKeys'},
'linked_servers': {'key': 'linkedServers', 'type': '[RedisLinkedServer]'},
'instances': {'key': 'instances', 'type': '[RedisInstanceDetails]'},
'private_endpoint_connections': {'key': 'privateEndpointConnections', 'type': '[PrivateEndpointConnection]'},
}
def __init__(
self,
*,
sku: "Sku",
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
subnet_id: Optional[str] = None,
static_ip: Optional[str] = None,
**kwargs
):
"""
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: Required. The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
:keyword subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:paramtype subnet_id: str
:keyword static_ip: Static IP address. Optionally, may be specified when deploying a Redis
cache inside an existing Azure Virtual Network; auto assigned by default.
:paramtype static_ip: str
"""
super(RedisProperties, self).__init__(redis_configuration=redis_configuration, redis_version=redis_version, enable_non_ssl_port=enable_non_ssl_port, replicas_per_master=replicas_per_master, replicas_per_primary=replicas_per_primary, tenant_settings=tenant_settings, shard_count=shard_count, minimum_tls_version=minimum_tls_version, public_network_access=public_network_access, sku=sku, subnet_id=subnet_id, static_ip=static_ip, **kwargs)
self.provisioning_state = None
self.host_name = None
self.port = None
self.ssl_port = None
self.access_keys = None
self.linked_servers = None
self.instances = None
self.private_endpoint_connections = None
class RedisRebootParameters(msrest.serialization.Model):
"""Specifies which Redis node(s) to reboot.
:ivar reboot_type: Which Redis node(s) to reboot. Depending on this value data loss is
possible. Possible values include: "PrimaryNode", "SecondaryNode", "AllNodes".
:vartype reboot_type: str or ~azure.mgmt.redis.models.RebootType
:ivar shard_id: If clustering is enabled, the ID of the shard to be rebooted.
:vartype shard_id: int
:ivar ports: A list of redis instances to reboot, specified by per-instance SSL ports or
non-SSL ports.
:vartype ports: list[int]
"""
_attribute_map = {
'reboot_type': {'key': 'rebootType', 'type': 'str'},
'shard_id': {'key': 'shardId', 'type': 'int'},
'ports': {'key': 'ports', 'type': '[int]'},
}
def __init__(
self,
*,
reboot_type: Optional[Union[str, "RebootType"]] = None,
shard_id: Optional[int] = None,
ports: Optional[List[int]] = None,
**kwargs
):
"""
:keyword reboot_type: Which Redis node(s) to reboot. Depending on this value data loss is
possible. Possible values include: "PrimaryNode", "SecondaryNode", "AllNodes".
:paramtype reboot_type: str or ~azure.mgmt.redis.models.RebootType
:keyword shard_id: If clustering is enabled, the ID of the shard to be rebooted.
:paramtype shard_id: int
:keyword ports: A list of redis instances to reboot, specified by per-instance SSL ports or
non-SSL ports.
:paramtype ports: list[int]
"""
super(RedisRebootParameters, self).__init__(**kwargs)
self.reboot_type = reboot_type
self.shard_id = shard_id
self.ports = ports
class RedisRegenerateKeyParameters(msrest.serialization.Model):
"""Specifies which Redis access keys to reset.
All required parameters must be populated in order to send to Azure.
:ivar key_type: Required. The Redis access key to regenerate. Possible values include:
"Primary", "Secondary".
:vartype key_type: str or ~azure.mgmt.redis.models.RedisKeyType
"""
_validation = {
'key_type': {'required': True},
}
_attribute_map = {
'key_type': {'key': 'keyType', 'type': 'str'},
}
def __init__(
self,
*,
key_type: Union[str, "RedisKeyType"],
**kwargs
):
"""
:keyword key_type: Required. The Redis access key to regenerate. Possible values include:
"Primary", "Secondary".
:paramtype key_type: str or ~azure.mgmt.redis.models.RedisKeyType
"""
super(RedisRegenerateKeyParameters, self).__init__(**kwargs)
self.key_type = key_type
class TrackedResource(Resource):
"""The resource model definition for an Azure Resource Manager tracked top level resource which has 'tags' and a 'location'.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar tags: A set of tags. Resource tags.
:vartype tags: dict[str, str]
:ivar location: Required. The geo-location where the resource lives.
:vartype location: str
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
}
def __init__(
self,
*,
location: str,
tags: Optional[Dict[str, str]] = None,
**kwargs
):
"""
:keyword tags: A set of tags. Resource tags.
:paramtype tags: dict[str, str]
:keyword location: Required. The geo-location where the resource lives.
:paramtype location: str
"""
super(TrackedResource, self).__init__(**kwargs)
self.tags = tags
self.location = location
class RedisResource(TrackedResource):
"""A single Redis item in List or Get Operation.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
:ivar id: Fully qualified resource ID for the resource. Ex -
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
:vartype id: str
:ivar name: The name of the resource.
:vartype name: str
:ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
"Microsoft.Storage/storageAccounts".
:vartype type: str
:ivar tags: A set of tags. Resource tags.
:vartype tags: dict[str, str]
:ivar location: Required. The geo-location where the resource lives.
:vartype location: str
:ivar zones: A list of availability zones denoting where the resource needs to come from.
:vartype zones: list[str]
:ivar identity: The identity of the resource.
:vartype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: Required. The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
:ivar subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:vartype subnet_id: str
:ivar static_ip: Static IP address. Optionally, may be specified when deploying a Redis cache
inside an existing Azure Virtual Network; auto assigned by default.
:vartype static_ip: str
:ivar provisioning_state: Redis instance provisioning status. Possible values include:
"Creating", "Deleting", "Disabled", "Failed", "Linking", "Provisioning",
"RecoveringScaleFailure", "Scaling", "Succeeded", "Unlinking", "Unprovisioning", "Updating".
:vartype provisioning_state: str or ~azure.mgmt.redis.models.ProvisioningState
:ivar host_name: Redis host name.
:vartype host_name: str
:ivar port: Redis non-SSL port.
:vartype port: int
:ivar ssl_port: Redis SSL port.
:vartype ssl_port: int
:ivar access_keys: The keys of the Redis cache - not set if this object is not the response to
Create or Update redis cache.
:vartype access_keys: ~azure.mgmt.redis.models.RedisAccessKeys
:ivar linked_servers: List of the linked servers associated with the cache.
:vartype linked_servers: list[~azure.mgmt.redis.models.RedisLinkedServer]
:ivar instances: List of the Redis instances associated with the cache.
:vartype instances: list[~azure.mgmt.redis.models.RedisInstanceDetails]
:ivar private_endpoint_connections: List of private endpoint connection associated with the
specified redis cache.
:vartype private_endpoint_connections: list[~azure.mgmt.redis.models.PrivateEndpointConnection]
"""
_validation = {
'id': {'readonly': True},
'name': {'readonly': True},
'type': {'readonly': True},
'location': {'required': True},
'sku': {'required': True},
'subnet_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'},
'static_ip': {'pattern': r'^\d+\.\d+\.\d+\.\d+$'},
'provisioning_state': {'readonly': True},
'host_name': {'readonly': True},
'port': {'readonly': True},
'ssl_port': {'readonly': True},
'access_keys': {'readonly': True},
'linked_servers': {'readonly': True},
'instances': {'readonly': True},
'private_endpoint_connections': {'readonly': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'type': {'key': 'type', 'type': 'str'},
'tags': {'key': 'tags', 'type': '{str}'},
'location': {'key': 'location', 'type': 'str'},
'zones': {'key': 'zones', 'type': '[str]'},
'identity': {'key': 'identity', 'type': 'ManagedServiceIdentity'},
'redis_configuration': {'key': 'properties.redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'properties.redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'properties.enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'properties.replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'properties.replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'properties.tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'properties.shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'properties.minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'properties.publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'properties.sku', 'type': 'Sku'},
'subnet_id': {'key': 'properties.subnetId', 'type': 'str'},
'static_ip': {'key': 'properties.staticIP', 'type': 'str'},
'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'},
'host_name': {'key': 'properties.hostName', 'type': 'str'},
'port': {'key': 'properties.port', 'type': 'int'},
'ssl_port': {'key': 'properties.sslPort', 'type': 'int'},
'access_keys': {'key': 'properties.accessKeys', 'type': 'RedisAccessKeys'},
'linked_servers': {'key': 'properties.linkedServers', 'type': '[RedisLinkedServer]'},
'instances': {'key': 'properties.instances', 'type': '[RedisInstanceDetails]'},
'private_endpoint_connections': {'key': 'properties.privateEndpointConnections', 'type': '[PrivateEndpointConnection]'},
}
def __init__(
self,
*,
location: str,
sku: "Sku",
tags: Optional[Dict[str, str]] = None,
zones: Optional[List[str]] = None,
identity: Optional["ManagedServiceIdentity"] = None,
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
subnet_id: Optional[str] = None,
static_ip: Optional[str] = None,
**kwargs
):
"""
:keyword tags: A set of tags. Resource tags.
:paramtype tags: dict[str, str]
:keyword location: Required. The geo-location where the resource lives.
:paramtype location: str
:keyword zones: A list of availability zones denoting where the resource needs to come from.
:paramtype zones: list[str]
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: Required. The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
:keyword subnet_id: The full resource ID of a subnet in a virtual network to deploy the Redis
cache in. Example format:
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/Microsoft.{Network|ClassicNetwork}/VirtualNetworks/vnet1/subnets/subnet1.
:paramtype subnet_id: str
:keyword static_ip: Static IP address. Optionally, may be specified when deploying a Redis
cache inside an existing Azure Virtual Network; auto assigned by default.
:paramtype static_ip: str
"""
super(RedisResource, self).__init__(tags=tags, location=location, **kwargs)
self.zones = zones
self.identity = identity
self.redis_configuration = redis_configuration
self.redis_version = redis_version
self.enable_non_ssl_port = enable_non_ssl_port
self.replicas_per_master = replicas_per_master
self.replicas_per_primary = replicas_per_primary
self.tenant_settings = tenant_settings
self.shard_count = shard_count
self.minimum_tls_version = minimum_tls_version
self.public_network_access = public_network_access
self.sku = sku
self.subnet_id = subnet_id
self.static_ip = static_ip
self.provisioning_state = None
self.host_name = None
self.port = None
self.ssl_port = None
self.access_keys = None
self.linked_servers = None
self.instances = None
self.private_endpoint_connections = None
class RedisUpdateParameters(msrest.serialization.Model):
"""Parameters supplied to the Update Redis operation.
:ivar tags: A set of tags. Resource tags.
:vartype tags: dict[str, str]
:ivar identity: The identity of the resource.
:vartype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
"""
_attribute_map = {
'tags': {'key': 'tags', 'type': '{str}'},
'identity': {'key': 'identity', 'type': 'ManagedServiceIdentity'},
'redis_configuration': {'key': 'properties.redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'properties.redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'properties.enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'properties.replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'properties.replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'properties.tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'properties.shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'properties.minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'properties.publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'properties.sku', 'type': 'Sku'},
}
def __init__(
self,
*,
tags: Optional[Dict[str, str]] = None,
identity: Optional["ManagedServiceIdentity"] = None,
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
sku: Optional["Sku"] = None,
**kwargs
):
"""
:keyword tags: A set of tags. Resource tags.
:paramtype tags: dict[str, str]
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.redis.models.ManagedServiceIdentity
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
"""
super(RedisUpdateParameters, self).__init__(**kwargs)
self.tags = tags
self.identity = identity
self.redis_configuration = redis_configuration
self.redis_version = redis_version
self.enable_non_ssl_port = enable_non_ssl_port
self.replicas_per_master = replicas_per_master
self.replicas_per_primary = replicas_per_primary
self.tenant_settings = tenant_settings
self.shard_count = shard_count
self.minimum_tls_version = minimum_tls_version
self.public_network_access = public_network_access
self.sku = sku
class RedisUpdateProperties(RedisCommonProperties):
"""Patchable properties of the redis cache.
:ivar redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:vartype redis_configuration: ~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:ivar redis_version: Redis version. Only major version will be used in PUT/PATCH request with
current valid values: (4, 6).
:vartype redis_version: str
:ivar enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is enabled.
:vartype enable_non_ssl_port: bool
:ivar replicas_per_master: The number of replicas to be created per primary.
:vartype replicas_per_master: int
:ivar replicas_per_primary: The number of replicas to be created per primary.
:vartype replicas_per_primary: int
:ivar tenant_settings: A dictionary of tenant settings.
:vartype tenant_settings: dict[str, str]
:ivar shard_count: The number of shards to be created on a Premium Cluster Cache.
:vartype shard_count: int
:ivar minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:vartype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:ivar public_network_access: Whether or not public endpoint access is allowed for this cache.
Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled', private
endpoints are the exclusive access method. Default value is 'Enabled'. Possible values include:
"Enabled", "Disabled". Default value: "Enabled".
:vartype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:ivar sku: The SKU of the Redis cache to deploy.
:vartype sku: ~azure.mgmt.redis.models.Sku
"""
_attribute_map = {
'redis_configuration': {'key': 'redisConfiguration', 'type': 'RedisCommonPropertiesRedisConfiguration'},
'redis_version': {'key': 'redisVersion', 'type': 'str'},
'enable_non_ssl_port': {'key': 'enableNonSslPort', 'type': 'bool'},
'replicas_per_master': {'key': 'replicasPerMaster', 'type': 'int'},
'replicas_per_primary': {'key': 'replicasPerPrimary', 'type': 'int'},
'tenant_settings': {'key': 'tenantSettings', 'type': '{str}'},
'shard_count': {'key': 'shardCount', 'type': 'int'},
'minimum_tls_version': {'key': 'minimumTlsVersion', 'type': 'str'},
'public_network_access': {'key': 'publicNetworkAccess', 'type': 'str'},
'sku': {'key': 'sku', 'type': 'Sku'},
}
def __init__(
self,
*,
redis_configuration: Optional["RedisCommonPropertiesRedisConfiguration"] = None,
redis_version: Optional[str] = None,
enable_non_ssl_port: Optional[bool] = False,
replicas_per_master: Optional[int] = None,
replicas_per_primary: Optional[int] = None,
tenant_settings: Optional[Dict[str, str]] = None,
shard_count: Optional[int] = None,
minimum_tls_version: Optional[Union[str, "TlsVersion"]] = None,
public_network_access: Optional[Union[str, "PublicNetworkAccess"]] = "Enabled",
sku: Optional["Sku"] = None,
**kwargs
):
"""
:keyword redis_configuration: All Redis Settings. Few possible keys:
rdb-backup-enabled,rdb-storage-connection-string,rdb-backup-frequency,maxmemory-delta,maxmemory-policy,notify-keyspace-events,maxmemory-samples,slowlog-log-slower-than,slowlog-max-len,list-max-ziplist-entries,list-max-ziplist-value,hash-max-ziplist-entries,hash-max-ziplist-value,set-max-intset-entries,zset-max-ziplist-entries,zset-max-ziplist-value
etc.
:paramtype redis_configuration:
~azure.mgmt.redis.models.RedisCommonPropertiesRedisConfiguration
:keyword redis_version: Redis version. Only major version will be used in PUT/PATCH request
with current valid values: (4, 6).
:paramtype redis_version: str
:keyword enable_non_ssl_port: Specifies whether the non-ssl Redis server port (6379) is
enabled.
:paramtype enable_non_ssl_port: bool
:keyword replicas_per_master: The number of replicas to be created per primary.
:paramtype replicas_per_master: int
:keyword replicas_per_primary: The number of replicas to be created per primary.
:paramtype replicas_per_primary: int
:keyword tenant_settings: A dictionary of tenant settings.
:paramtype tenant_settings: dict[str, str]
:keyword shard_count: The number of shards to be created on a Premium Cluster Cache.
:paramtype shard_count: int
:keyword minimum_tls_version: Optional: requires clients to use a specified TLS version (or
higher) to connect (e,g, '1.0', '1.1', '1.2'). Possible values include: "1.0", "1.1", "1.2".
:paramtype minimum_tls_version: str or ~azure.mgmt.redis.models.TlsVersion
:keyword public_network_access: Whether or not public endpoint access is allowed for this
cache. Value is optional but if passed in, must be 'Enabled' or 'Disabled'. If 'Disabled',
private endpoints are the exclusive access method. Default value is 'Enabled'. Possible values
include: "Enabled", "Disabled". Default value: "Enabled".
:paramtype public_network_access: str or ~azure.mgmt.redis.models.PublicNetworkAccess
:keyword sku: The SKU of the Redis cache to deploy.
:paramtype sku: ~azure.mgmt.redis.models.Sku
"""
super(RedisUpdateProperties, self).__init__(redis_configuration=redis_configuration, redis_version=redis_version, enable_non_ssl_port=enable_non_ssl_port, replicas_per_master=replicas_per_master, replicas_per_primary=replicas_per_primary, tenant_settings=tenant_settings, shard_count=shard_count, minimum_tls_version=minimum_tls_version, public_network_access=public_network_access, **kwargs)
self.sku = sku
class ScheduleEntry(msrest.serialization.Model):
"""Patch schedule entry for a Premium Redis Cache.
All required parameters must be populated in order to send to Azure.
:ivar day_of_week: Required. Day of the week when a cache can be patched. Possible values
include: "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday",
"Everyday", "Weekend".
:vartype day_of_week: str or ~azure.mgmt.redis.models.DayOfWeek
:ivar start_hour_utc: Required. Start hour after which cache patching can start.
:vartype start_hour_utc: int
:ivar maintenance_window: ISO8601 timespan specifying how much time cache patching can take.
:vartype maintenance_window: ~datetime.timedelta
"""
_validation = {
'day_of_week': {'required': True},
'start_hour_utc': {'required': True},
}
_attribute_map = {
'day_of_week': {'key': 'dayOfWeek', 'type': 'str'},
'start_hour_utc': {'key': 'startHourUtc', 'type': 'int'},
'maintenance_window': {'key': 'maintenanceWindow', 'type': 'duration'},
}
def __init__(
self,
*,
day_of_week: Union[str, "DayOfWeek"],
start_hour_utc: int,
maintenance_window: Optional[datetime.timedelta] = None,
**kwargs
):
"""
:keyword day_of_week: Required. Day of the week when a cache can be patched. Possible values
include: "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday",
"Everyday", "Weekend".
:paramtype day_of_week: str or ~azure.mgmt.redis.models.DayOfWeek
:keyword start_hour_utc: Required. Start hour after which cache patching can start.
:paramtype start_hour_utc: int
:keyword maintenance_window: ISO8601 timespan specifying how much time cache patching can take.
:paramtype maintenance_window: ~datetime.timedelta
"""
super(ScheduleEntry, self).__init__(**kwargs)
self.day_of_week = day_of_week
self.start_hour_utc = start_hour_utc
self.maintenance_window = maintenance_window
class Sku(msrest.serialization.Model):
"""SKU parameters supplied to the create Redis operation.
All required parameters must be populated in order to send to Azure.
:ivar name: Required. The type of Redis cache to deploy. Valid values: (Basic, Standard,
Premium). Possible values include: "Basic", "Standard", "Premium".
:vartype name: str or ~azure.mgmt.redis.models.SkuName
:ivar family: Required. The SKU family to use. Valid values: (C, P). (C = Basic/Standard, P =
Premium). Possible values include: "C", "P".
:vartype family: str or ~azure.mgmt.redis.models.SkuFamily
:ivar capacity: Required. The size of the Redis cache to deploy. Valid values: for C
(Basic/Standard) family (0, 1, 2, 3, 4, 5, 6), for P (Premium) family (1, 2, 3, 4).
:vartype capacity: int
"""
_validation = {
'name': {'required': True},
'family': {'required': True},
'capacity': {'required': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'family': {'key': 'family', 'type': 'str'},
'capacity': {'key': 'capacity', 'type': 'int'},
}
def __init__(
self,
*,
name: Union[str, "SkuName"],
family: Union[str, "SkuFamily"],
capacity: int,
**kwargs
):
"""
:keyword name: Required. The type of Redis cache to deploy. Valid values: (Basic, Standard,
Premium). Possible values include: "Basic", "Standard", "Premium".
:paramtype name: str or ~azure.mgmt.redis.models.SkuName
:keyword family: Required. The SKU family to use. Valid values: (C, P). (C = Basic/Standard, P
= Premium). Possible values include: "C", "P".
:paramtype family: str or ~azure.mgmt.redis.models.SkuFamily
:keyword capacity: Required. The size of the Redis cache to deploy. Valid values: for C
(Basic/Standard) family (0, 1, 2, 3, 4, 5, 6), for P (Premium) family (1, 2, 3, 4).
:paramtype capacity: int
"""
super(Sku, self).__init__(**kwargs)
self.name = name
self.family = family
self.capacity = capacity
class UpgradeNotification(msrest.serialization.Model):
"""Properties of upgrade notification.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar name: Name of upgrade notification.
:vartype name: str
:ivar timestamp: Timestamp when upgrade notification occurred.
:vartype timestamp: ~datetime.datetime
:ivar upsell_notification: Details about this upgrade notification.
:vartype upsell_notification: dict[str, str]
"""
_validation = {
'name': {'readonly': True},
'timestamp': {'readonly': True},
'upsell_notification': {'readonly': True},
}
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'timestamp': {'key': 'timestamp', 'type': 'iso-8601'},
'upsell_notification': {'key': 'upsellNotification', 'type': '{str}'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(UpgradeNotification, self).__init__(**kwargs)
self.name = None
self.timestamp = None
self.upsell_notification = None
class UserAssignedIdentity(msrest.serialization.Model):
"""User assigned identity properties.
Variables are only populated by the server, and will be ignored when sending a request.
:ivar principal_id: The principal ID of the assigned identity.
:vartype principal_id: str
:ivar client_id: The client ID of the assigned identity.
:vartype client_id: str
"""
_validation = {
'principal_id': {'readonly': True},
'client_id': {'readonly': True},
}
_attribute_map = {
'principal_id': {'key': 'principalId', 'type': 'str'},
'client_id': {'key': 'clientId', 'type': 'str'},
}
def __init__(
self,
**kwargs
):
"""
"""
super(UserAssignedIdentity, self).__init__(**kwargs)
self.principal_id = None
self.client_id = None
| 45.905874 | 445 | 0.674092 | 15,136 | 129,730 | 5.625991 | 0.040499 | 0.01455 | 0.020222 | 0.028889 | 0.837015 | 0.807657 | 0.787364 | 0.760002 | 0.742916 | 0.728225 | 0 | 0.00314 | 0.211986 | 129,730 | 2,825 | 446 | 45.922124 | 0.829843 | 0.550212 | 0 | 0.666941 | 0 | 0 | 0.256253 | 0.079949 | 0 | 0 | 0 | 0 | 0 | 1 | 0.040296 | false | 0 | 0.005757 | 0 | 0.158717 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3c827c5aeedeef130bb395174abdc3324c33f62b | 254 | py | Python | RQ2_ros_implementation/turtlebot-runner/tactics/ee3/ee3.py | S2-group/msr-2021-robotics-green-architectural-tactics-replication-package | fc4a205b00abb0b096c472856002e440e73f2c5d | [
"MIT"
] | 2 | 2021-03-26T17:29:27.000Z | 2021-03-27T20:06:21.000Z | RQ2_ros_implementation/turtlebot-runner/tactics/ee3/ee3.py | S2-group/msr-2021-robotics-green-architectural-tactics-replication-package | fc4a205b00abb0b096c472856002e440e73f2c5d | [
"MIT"
] | null | null | null | RQ2_ros_implementation/turtlebot-runner/tactics/ee3/ee3.py | S2-group/msr-2021-robotics-green-architectural-tactics-replication-package | fc4a205b00abb0b096c472856002e440e73f2c5d | [
"MIT"
] | null | null | null | from tactics.ee3.EE3CameraController import CameraController
class EE3:
__camera_controller: CameraController
def __init__(self):
self.__camera_controller = CameraController()
def exit(self):
self.__camera_controller.exit() | 25.4 | 60 | 0.748031 | 25 | 254 | 7.08 | 0.52 | 0.271186 | 0.361582 | 0.39548 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.014423 | 0.181102 | 254 | 10 | 61 | 25.4 | 0.836538 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.142857 | 0 | 0.714286 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 6 |
b1ee0d605611f820ff72d5de9e55516a9d2c1002 | 2,107 | py | Python | src/data_handling/DataClasses.py | marcopost-it/TaughtNet | 3d5d15e6d16c5592aa36ee59867e322f0353fee9 | [
"Apache-2.0"
] | null | null | null | src/data_handling/DataClasses.py | marcopost-it/TaughtNet | 3d5d15e6d16c5592aa36ee59867e322f0353fee9 | [
"Apache-2.0"
] | null | null | null | src/data_handling/DataClasses.py | marcopost-it/TaughtNet | 3d5d15e6d16c5592aa36ee59867e322f0353fee9 | [
"Apache-2.0"
] | null | null | null | from dataclasses import dataclass
from enum import Enum
from typing import Dict, List, Optional, Union, Tuple
@dataclass
class InputExample:
"""
A single training/test example for token classification.
Args:
guid: Unique id for the example.
words: list. The words of the sequence.
labels: (Optional) list. The labels for each word of the sequence. This should be
specified for train and dev examples, but not for test examples.
"""
guid: str
words: List[str]
labels: Optional[List[str]]
@dataclass
class KGInputExample:
"""
A single training/test example for token classification.
Args:
guid: Unique id for the example.
words: list. The words of the sequence.
labels: (Optional) list. The labels for each word of the sequence. This should be
specified for train and dev examples, but not for test examples.
"""
guid: str
words: List[str]
labels: Optional[List[str]]
teachers_proba: Optional[List[List[float]]]
@dataclass
class InputFeatures:
"""
A single set of features of data.
Property names are the same names as the corresponding inputs to a model.
"""
input_ids: List[int]
attention_mask: List[int]
token_type_ids: Optional[List[int]] = None
label_ids: Optional[List[int]] = None
@dataclass
class KGInputFeatures:
"""
A single set of features of data.
Property names are the same names as the corresponding inputs to a model.
"""
input_ids: List[int]
attention_mask: List[int]
token_type_ids: Optional[List[int]] = None
label_ids: Optional[List[int]] = None
teachers_proba: Optional[List[List[float]]] = None
@dataclass
class SequenceInputFeatures:
"""
A single set of features of data.
Property names are the same names as the corresponding inputs to a model.
"""
input_ids: List[int]
attention_mask: List[int]
token_type_ids: Optional[List[int]] = None
label_ids: Optional[List[int]] = None
class Split(Enum):
train = "train"
dev = "dev"
test = "test" | 27.363636 | 89 | 0.675368 | 288 | 2,107 | 4.881944 | 0.246528 | 0.102418 | 0.064011 | 0.076814 | 0.802987 | 0.802987 | 0.754623 | 0.754623 | 0.754623 | 0.754623 | 0 | 0 | 0.239677 | 2,107 | 77 | 90 | 27.363636 | 0.877653 | 0.437114 | 0 | 0.621622 | 0 | 0 | 0.011331 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.081081 | 0 | 0.864865 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
593598ba4ef1ea9849e1dbdc1f79686e0a3b2531 | 2,367 | py | Python | petstagram/main_app/forms.py | rashkov7/petstagram | 1589da79acb37ffa07a56a3f7426bc76b9db12b0 | [
"MIT"
] | null | null | null | petstagram/main_app/forms.py | rashkov7/petstagram | 1589da79acb37ffa07a56a3f7426bc76b9db12b0 | [
"MIT"
] | 3 | 2022-03-22T21:29:56.000Z | 2022-03-23T07:13:30.000Z | petstagram/main_app/forms.py | rashkov7/petstagram | 1589da79acb37ffa07a56a3f7426bc76b9db12b0 | [
"MIT"
] | null | null | null | from django import forms
from django.core.exceptions import NON_FIELD_ERRORS
from petstagram.main_app.models import Pet, PetPhoto
class PetCreateForm(forms.ModelForm):
class Meta:
model = Pet
exclude = ('user_profile',)
error_messages = {
NON_FIELD_ERRORS: {
'unique_together': "%(model_name)s's %(field_labels)s are not unique.",
}
}
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for _, field in self.fields.items():
if hasattr(field, 'class'):
field.widget.attrs['class'] = 'form-control'
field.widget.attrs.update({'class': 'form-control'})
class PhotoCreateForm(forms.ModelForm):
class Meta:
model = PetPhoto
fields = '__all__'
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for _, field in self.fields.items():
if hasattr(field, 'class'):
field.widget.attrs['class'] = 'form-control'
field.widget.attrs.update({'class': 'form-control'})
class PhotoEditForm(forms.ModelForm):
class Meta:
model = PetPhoto
exclude = ('likes',)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for _, field in self.fields.items():
if hasattr(field, 'class'):
field.widget.attrs['class'] = 'form-control'
field.widget.attrs.update({'class': 'form-control'})
class PetEditForm(forms.ModelForm):
class Meta:
model = Pet
exclude = ('user_profile',)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for _, field in self.fields.items():
if hasattr(field, 'class'):
field.widget.attrs['class'] = 'form-control'
field.widget.attrs.update({'class': 'form-control'})
class PetDeleteForm(forms.ModelForm):
class Meta:
model = Pet
exclude = ('user_profile',)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for _, field in self.fields.items():
if hasattr(field, 'class'):
field.widget.attrs['class'] = 'form-control'
field.widget.attrs.update({'class': 'form-control', 'readonly': 'readonly'})
| 31.56 | 88 | 0.575412 | 252 | 2,367 | 5.162698 | 0.222222 | 0.076864 | 0.122982 | 0.088394 | 0.775557 | 0.775557 | 0.720215 | 0.720215 | 0.720215 | 0.682552 | 0 | 0 | 0.277567 | 2,367 | 74 | 89 | 31.986486 | 0.760819 | 0 | 0 | 0.724138 | 0 | 0 | 0.13646 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.086207 | false | 0 | 0.051724 | 0 | 0.310345 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
59475df3dcebc1b72c75e406df9b9ee262397fe3 | 4,222 | py | Python | app/region/trainEcoRegion.py | fkwai/geolearn | 30cb4353d22af5020a48100d07ab04f465a315b0 | [
"MIT"
] | null | null | null | app/region/trainEcoRegion.py | fkwai/geolearn | 30cb4353d22af5020a48100d07ab04f465a315b0 | [
"MIT"
] | null | null | null | app/region/trainEcoRegion.py | fkwai/geolearn | 30cb4353d22af5020a48100d07ab04f465a315b0 | [
"MIT"
] | 2 | 2021-04-04T02:45:59.000Z | 2022-03-19T09:41:39.000Z | from hydroDL import pathSMAP, master
import os
from hydroDL.data import dbCsv
# train for each cont
subsetLst = ['ecoRegion{0:0>2}_v2f1'.format(x) for x in range(1, 18)]
caseLst = ['Forcing', 'Soilm']
# train a CONUS model
cid = 1
for case in caseLst:
if case == 'Forcing':
varLst = dbCsv.varForcing
else:
varLst = dbCsv.varSoilM
optData = master.default.update(
master.default.optDataSMAP,
rootDB=pathSMAP['DB_L3_NA'],
subset='CONUSv2f1',
tRange=[20150401, 20160401],
varT=varLst)
optModel = master.default.optLstm
optLoss = master.default.optLossRMSE
optTrain = master.default.optTrainSMAP
out = os.path.join(pathSMAP['Out_L3_NA'], 'CONUSv2f1_' + case)
masterDict = master.wrapMaster(out, optData, optModel, optLoss, optTrain)
master.runTrain(masterDict, cudaID=cid % 3, screen=case)
cid = cid + 1
# train for each region
cid = 0
for k in range(len(subsetLst)):
for case in caseLst:
if case == 'Forcing':
varLst = dbCsv.varForcing
else:
varLst = dbCsv.varSoilM
optData = master.default.update(
master.default.optDataSMAP,
rootDB=pathSMAP['DB_L3_NA'],
subset=subsetLst[k],
tRange=[20150401, 20160401],
varT=varLst)
optModel = master.default.optLstm
optLoss = master.default.optLossRMSE
optTrain = master.default.optTrainSMAP
out = os.path.join(pathSMAP['Out_L3_NA'], 'ecoRegion',
subsetLst[k] + '_' + case)
masterDict = master.wrapMaster(out, optData, optModel, optLoss,
optTrain)
# master.runTrain(masterDict, cudaID=cid % 3, screen=subsetLst[k])
cid = cid + 1
# master.train(masterDict)
# retrain some models
rtEcoLst = [1, 2, 5, 7, 8, 10, 13, 16, 17]
rtCaseLst = [
'Forcing', 'SoilM', 'SoilM', 'Forcing', 'SoilM', 'Forcing', 'Forcing',
'Forcing', 'SoilM'
]
cid = 0
for kk in range(len(rtEcoLst)):
k = rtEcoLst[kk] - 1
case = rtCaseLst[kk]
optData = master.default.update(
master.default.optDataSMAP,
rootDB=pathSMAP['DB_L3_NA'],
subset=subsetLst[k],
tRange=[20150401, 20160401],
varT=varLst)
optModel = master.default.optLstm
optLoss = master.default.optLossRMSE
optTrain = master.default.optTrainSMAP
out = os.path.join(pathSMAP['Out_L3_NA'], 'ecoRegion',
subsetLst[k] + '_' + case)
masterDict = master.wrapMaster(out, optData, optModel, optLoss, optTrain)
master.runTrain(masterDict, cudaID=cid % 3, screen=subsetLst[k])
cid = cid + 1
# master.train(masterDict)
# test
ss = ''
for k in range(len(subsetLst)):
for case in caseLst:
out = os.path.join(pathSMAP['Out_L3_NA'], 'ecoRegion',
subsetLst[k] + '_' + case)
try:
master.test(out, tRange=[20160401, 20180401], subset=subsetLst[k])
except:
ss = ss + 'ecoRegion ' + str(k) + ' case ' + case + '; '
# retrain some models
# rtEcoLst = [1, 2, 5, 7, 8, 10, 13, 16, 17]
# rtCaseLst = [
# 'Forcing', 'Soilm', 'Soilm', 'Forcing', 'Soilm', 'Forcing', 'Forcing',
# 'Forcing', 'Soilm'
# ]
# rtEcoLst = [1, 4, 7, 16]
# rtCaseLst = ['Soilm', 'Soilm', 'Soilm', 'Soilm']
# cid = 2
# for kk in range(len(rtEcoLst)):
# k = rtEcoLst[kk] - 1
# case = rtCaseLst[kk]
# if case == 'Forcing':
# varLst = dbCsv.varForcing
# else:
# varLst = dbCsv.varSoilM
# optData = master.default.update(
# master.default.optDataSMAP,
# rootDB=pathSMAP['DB_L3_NA'],
# subset=subsetLst[k],
# tRange=[20150401, 20160401],
# varT=varLst)
# optModel = master.default.optLstm
# optLoss = master.default.optLossRMSE
# optTrain = master.default.optTrainSMAP
# out = os.path.join(pathSMAP['Out_L3_NA'], 'ecoRegion',
# subsetLst[k] + '_' + case)
# masterDict = master.wrapMaster(out, optData, optModel, optLoss, optTrain)
# master.runTrain(masterDict, cudaID=cid % 3, screen=subsetLst[k])
# cid = cid + 1
# # master.train(masterDict) | 34.325203 | 79 | 0.598532 | 478 | 4,222 | 5.236402 | 0.1841 | 0.103875 | 0.017978 | 0.025969 | 0.856972 | 0.856972 | 0.856972 | 0.856972 | 0.856972 | 0.856972 | 0 | 0.047051 | 0.26504 | 4,222 | 123 | 80 | 34.325203 | 0.759588 | 0.300095 | 0 | 0.675325 | 0 | 0 | 0.078559 | 0.007204 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.038961 | 0 | 0.038961 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3ca98a0a2df90826517ba589a44a9ec5b4dea853 | 55 | py | Python | 10_How_To_Get_Document.py | MoYuStudio/MoYuEngine | 7d9ab5c9cb268de0071e798a3288f0bbb651795e | [
"Apache-2.0"
] | 2 | 2022-03-22T02:32:34.000Z | 2022-03-22T02:32:43.000Z | 10_How_To_Get_Document.py | MoYuStudio/MoYuEngine | 7d9ab5c9cb268de0071e798a3288f0bbb651795e | [
"Apache-2.0"
] | null | null | null | 10_How_To_Get_Document.py | MoYuStudio/MoYuEngine | 7d9ab5c9cb268de0071e798a3288f0bbb651795e | [
"Apache-2.0"
] | null | null | null |
import moyu_engine
print(moyu_engine.Window.__doc__)
| 11 | 33 | 0.836364 | 8 | 55 | 5 | 0.75 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 55 | 4 | 34 | 13.75 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 6 |
3cddb5843873c93712e1da4b04c228e1d7bccea7 | 6,857 | py | Python | google/cloud/billing_budgets_v1beta1/proto/budget_service_pb2_grpc.py | dwsupplee/python-billingbudgets | bef9509b7f4cb6427ef4f0b27c57e0ba69694be7 | [
"Apache-2.0"
] | 1 | 2019-12-09T11:40:28.000Z | 2019-12-09T11:40:28.000Z | google/cloud/billing_budgets_v1beta1/proto/budget_service_pb2_grpc.py | dwsupplee/python-billingbudgets | bef9509b7f4cb6427ef4f0b27c57e0ba69694be7 | [
"Apache-2.0"
] | 40 | 2019-07-16T10:04:48.000Z | 2020-01-20T09:04:59.000Z | google/cloud/billing_budgets_v1beta1/proto/budget_service_pb2_grpc.py | dwsupplee/python-billingbudgets | bef9509b7f4cb6427ef4f0b27c57e0ba69694be7 | [
"Apache-2.0"
] | 2 | 2019-07-18T00:05:31.000Z | 2019-11-27T14:17:22.000Z | # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc
from google.cloud.billing_budgets_v1beta1.proto import (
budget_model_pb2 as google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2,
)
from google.cloud.billing_budgets_v1beta1.proto import (
budget_service_pb2 as google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2,
)
from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2
class BudgetServiceStub(object):
"""BudgetService stores Cloud Billing budgets, which define a
budget plan and rules to execute as we track spend against that plan.
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.CreateBudget = channel.unary_unary(
"/google.cloud.billing.budgets.v1beta1.BudgetService/CreateBudget",
request_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.CreateBudgetRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.FromString,
)
self.UpdateBudget = channel.unary_unary(
"/google.cloud.billing.budgets.v1beta1.BudgetService/UpdateBudget",
request_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.UpdateBudgetRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.FromString,
)
self.GetBudget = channel.unary_unary(
"/google.cloud.billing.budgets.v1beta1.BudgetService/GetBudget",
request_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.GetBudgetRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.FromString,
)
self.ListBudgets = channel.unary_unary(
"/google.cloud.billing.budgets.v1beta1.BudgetService/ListBudgets",
request_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.ListBudgetsRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.ListBudgetsResponse.FromString,
)
self.DeleteBudget = channel.unary_unary(
"/google.cloud.billing.budgets.v1beta1.BudgetService/DeleteBudget",
request_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.DeleteBudgetRequest.SerializeToString,
response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString,
)
class BudgetServiceServicer(object):
"""BudgetService stores Cloud Billing budgets, which define a
budget plan and rules to execute as we track spend against that plan.
"""
def CreateBudget(self, request, context):
"""Creates a new budget. See
<a href="https://cloud.google.com/billing/quotas">Quotas and limits</a>
for more information on the limits of the number of budgets you can create.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def UpdateBudget(self, request, context):
"""Updates a budget and returns the updated budget.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def GetBudget(self, request, context):
"""Returns a budget.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def ListBudgets(self, request, context):
"""Returns a list of budgets for a billing account.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def DeleteBudget(self, request, context):
"""Deletes a budget. Returns successfully if already deleted.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def add_BudgetServiceServicer_to_server(servicer, server):
rpc_method_handlers = {
"CreateBudget": grpc.unary_unary_rpc_method_handler(
servicer.CreateBudget,
request_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.CreateBudgetRequest.FromString,
response_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.SerializeToString,
),
"UpdateBudget": grpc.unary_unary_rpc_method_handler(
servicer.UpdateBudget,
request_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.UpdateBudgetRequest.FromString,
response_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.SerializeToString,
),
"GetBudget": grpc.unary_unary_rpc_method_handler(
servicer.GetBudget,
request_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.GetBudgetRequest.FromString,
response_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__model__pb2.Budget.SerializeToString,
),
"ListBudgets": grpc.unary_unary_rpc_method_handler(
servicer.ListBudgets,
request_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.ListBudgetsRequest.FromString,
response_serializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.ListBudgetsResponse.SerializeToString,
),
"DeleteBudget": grpc.unary_unary_rpc_method_handler(
servicer.DeleteBudget,
request_deserializer=google_dot_cloud_dot_billing_dot_budgets__v1beta1_dot_proto_dot_budget__service__pb2.DeleteBudgetRequest.FromString,
response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
"google.cloud.billing.budgets.v1beta1.BudgetService", rpc_method_handlers
)
server.add_generic_rpc_handlers((generic_handler,))
| 54.420635 | 155 | 0.774974 | 787 | 6,857 | 6.217281 | 0.144854 | 0.080114 | 0.057225 | 0.069487 | 0.791743 | 0.767832 | 0.752912 | 0.700593 | 0.700593 | 0.615573 | 0 | 0.014263 | 0.161587 | 6,857 | 125 | 156 | 54.856 | 0.836841 | 0.108211 | 0 | 0.318182 | 1 | 0 | 0.107983 | 0.060616 | 0 | 0 | 0 | 0 | 0 | 1 | 0.079545 | false | 0 | 0.045455 | 0 | 0.147727 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3ce3ada8327aa430d15f4f442545a6d8e78db186 | 2,800 | py | Python | transactions/migrations/0001_initial.py | Guilehm/expense-control-system | c0f8393497f54076cb15008f1bda9efc5081025b | [
"MIT"
] | 1 | 2022-02-16T23:23:02.000Z | 2022-02-16T23:23:02.000Z | transactions/migrations/0001_initial.py | guilehm/expense-control-system | c0f8393497f54076cb15008f1bda9efc5081025b | [
"MIT"
] | 40 | 2018-07-01T15:49:05.000Z | 2018-09-06T02:37:24.000Z | transactions/migrations/0001_initial.py | Guilehm/Expense-Control-System | c0f8393497f54076cb15008f1bda9efc5081025b | [
"MIT"
] | 1 | 2019-05-05T13:43:55.000Z | 2019-05-05T13:43:55.000Z | # Generated by Django 2.0.5 on 2018-05-10 01:18
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('core', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Expense',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=50)),
('description', models.TextField(blank=True, null=True)),
('value', models.DecimalField(decimal_places=2, max_digits=9)),
('due_date', models.DateField(db_index=True)),
('paid_out', models.BooleanField(default=False)),
('note', models.TextField(blank=True, null=True)),
('slug', models.SlugField()),
('date_added', models.DateTimeField(auto_now_add=True, db_index=True)),
('date_changed', models.DateTimeField(auto_now=True, db_index=True)),
('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='expenses', to='core.Category')),
('tags', models.ManyToManyField(blank=True, related_name='expenses', to='core.Tag')),
('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='Revenue',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=50)),
('description', models.TextField(blank=True, null=True)),
('value', models.DecimalField(decimal_places=2, max_digits=9)),
('due_date', models.DateField(db_index=True)),
('received_out', models.BooleanField(default=False)),
('note', models.TextField(blank=True, null=True)),
('slug', models.SlugField()),
('date_added', models.DateTimeField(auto_now_add=True, db_index=True)),
('date_changed', models.DateTimeField(auto_now=True, db_index=True)),
('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='revenues', to='core.Category')),
('tags', models.ManyToManyField(blank=True, related_name='revenues', to='core.Tag')),
('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
]
| 50.909091 | 138 | 0.608214 | 300 | 2,800 | 5.516667 | 0.3 | 0.029003 | 0.039879 | 0.066465 | 0.8 | 0.780665 | 0.780665 | 0.780665 | 0.780665 | 0.780665 | 0 | 0.012766 | 0.244643 | 2,800 | 54 | 139 | 51.851852 | 0.76974 | 0.016071 | 0 | 0.595745 | 1 | 0 | 0.102434 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.06383 | 0 | 0.148936 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
a72782771fdbc7afe91fea9033dd0c72668b2af2 | 31 | py | Python | affnine_deltaleaf/__init__.py | biswanathamz/affnine_delta_leaf | 8c1e8736db81e9daaa5dbe46d1a67326c67ac679 | [
"MIT"
] | 4 | 2019-11-30T17:06:26.000Z | 2021-02-05T04:02:03.000Z | affnine_deltaleaf/__init__.py | biswanathamz/affnine_delta_leaf | 8c1e8736db81e9daaa5dbe46d1a67326c67ac679 | [
"MIT"
] | null | null | null | affnine_deltaleaf/__init__.py | biswanathamz/affnine_delta_leaf | 8c1e8736db81e9daaa5dbe46d1a67326c67ac679 | [
"MIT"
] | 2 | 2019-11-30T17:06:30.000Z | 2020-01-07T14:19:50.000Z | from .afn_algo import deltaLeaf | 31 | 31 | 0.870968 | 5 | 31 | 5.2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.096774 | 31 | 1 | 31 | 31 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
5970a47153234df990d88b304545ab817759b02a | 71 | py | Python | pyronear/models/__init__.py | JoaoFdC/PyroNear | ca56316d5ad986789feace9dd913115596f6c2ca | [
"MIT"
] | null | null | null | pyronear/models/__init__.py | JoaoFdC/PyroNear | ca56316d5ad986789feace9dd913115596f6c2ca | [
"MIT"
] | null | null | null | pyronear/models/__init__.py | JoaoFdC/PyroNear | ca56316d5ad986789feace9dd913115596f6c2ca | [
"MIT"
] | null | null | null | from .resnet import *
from .densenet import *
from .mobilenet import *
| 17.75 | 24 | 0.746479 | 9 | 71 | 5.888889 | 0.555556 | 0.377358 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.169014 | 71 | 3 | 25 | 23.666667 | 0.898305 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
59a636b1f793010269f338f094cc5302efcf81a8 | 96 | py | Python | venv/lib/python3.8/site-packages/debugpy/adapter/clients.py | Retraces/UkraineBot | 3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71 | [
"MIT"
] | 2 | 2022-03-13T01:58:52.000Z | 2022-03-31T06:07:54.000Z | venv/lib/python3.8/site-packages/debugpy/adapter/clients.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | 19 | 2021-11-20T04:09:18.000Z | 2022-03-23T15:05:55.000Z | venv/lib/python3.8/site-packages/debugpy/adapter/clients.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | null | null | null | /home/runner/.cache/pip/pool/45/c2/89/ad2a61d5929dffd2339f33635bbe9c0b6065cda6d2161117c47eb8c8ce | 96 | 96 | 0.895833 | 9 | 96 | 9.555556 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.40625 | 0 | 96 | 1 | 96 | 96 | 0.489583 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
59b50771f03759a1ad11a0366b87c6ac4a44d5c3 | 6,389 | py | Python | scripts/config.py | LevinRoman/MMORT | afdb4931b68d5679e9a8b9778c9ca7a2d6caf69c | [
"MIT"
] | null | null | null | scripts/config.py | LevinRoman/MMORT | afdb4931b68d5679e9a8b9778c9ca7a2d6caf69c | [
"MIT"
] | null | null | null | scripts/config.py | LevinRoman/MMORT | afdb4931b68d5679e9a8b9778c9ca7a2d6caf69c | [
"MIT"
] | null | null | null | import numpy as np
configurations = {}
#Experiment 1: Two modality, dosimetric difference
def experiment_1():
"""Config for Experiment 1: Two modality, dosimetric difference"""
configurations = {}
Alpha = np.array([0.35, 0.35])
Beta = np.array([0.175, 0.175])
Gamma = np.array([np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35])
])
Delta = np.array([np.array([0.07, 0.07]),
np.array([0.07, 0.07]),
np.array([0.175, 0.175]),
np.array([0.175, 0.175]),
np.array([0.175, 0.175])
])
modality_names = np.array(['Aphoton', 'Aproton'])
configurations['Alpha'] = Alpha
configurations['Beta'] = Beta
configurations['Gamma'] = Gamma
configurations['Delta'] = Delta
configurations['modality_names'] = modality_names
return configurations
#Experiment 2: photon IMRT objective using our code
def experiment_2(N1, d):
"""Config for Experiment 2: This experiment should
yield Tu-d as the objective where d is the target uniform dose per fraction"""
configurations = {}
Alpha = np.array([2*d/N1, 0.0])
Beta = np.array([-1/N1, 0.0])
Gamma = np.array([np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0])
])
Delta = np.array([np.array([0.07, 0.0]),
np.array([0.07, 0.0]),
np.array([0.175, 0.0]),
np.array([0.175, 0.0]),
np.array([0.175, 0.0])
])
modality_names = np.array(['Aphoton', 'Aproton'])
configurations['Alpha'] = Alpha
configurations['Beta'] = Beta
configurations['Gamma'] = Gamma
configurations['Delta'] = Delta
configurations['modality_names'] = modality_names
return configurations
#Experiment 3: proton IMRT objective using our code
def experiment_3(N1, d):
"""Config for Experiment 3: This experiment should
yield Tu-d as the objective where d is the target uniform dose per fraction and T is the second modality dose matrix"""
configurations = {}
Alpha = np.array([0.0, 2*d/N1])
Beta = np.array([0.0, -1/N1])
Gamma = np.array([np.array([0.0, 0.35]),
np.array([0.0, 0.35]),
np.array([0.0, 0.35]),
np.array([0.0, 0.35]),
np.array([0.0, 0.35])
])
Delta = np.array([np.array([0.0, 0.07]),
np.array([0.0, 0.07]),
np.array([0.0, 0.175]),
np.array([0.0, 0.175]),
np.array([0.0, 0.175])
])
modality_names = np.array(['Aphoton', 'Aproton'])
configurations['Alpha'] = Alpha
configurations['Beta'] = Beta
configurations['Gamma'] = Gamma
configurations['Delta'] = Delta
configurations['modality_names'] = modality_names
return configurations
#tumor max dose (tmd) multi-modality experiment
def experiment_tmd():
"""Config for Experiment 1: Two modality, dosimetric difference"""
configurations = {}
Alpha = np.array([0.35, 0.35])
Beta = np.array([0.175, 0.175])
Gamma = np.array([np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35]),
np.array([0.35, 0.35])
])
Delta = np.array([np.array([0.07, 0.07]),
np.array([0.07, 0.07]),
np.array([0.175, 0.175]),
np.array([0.175, 0.175]),
np.array([0.175, 0.175]),
np.array([0.175, 0.175])
])
modality_names = np.array(['Aphoton', 'Aproton'])
configurations['Alpha'] = Alpha
configurations['Beta'] = Beta
configurations['Gamma'] = Gamma
configurations['Delta'] = Delta
configurations['modality_names'] = modality_names
return configurations
#tumor max dose (tmd) IMRT experiment
def experiment_tmd_imrt(N1, d):
"""Config for Experiment 2: This experiment should
yield Tu-d as the objective where d is the target uniform dose per fraction"""
configurations = {}
Alpha = np.array([2*d/N1, 0.0])
Beta = np.array([-1/N1, 0.0])
Gamma = np.array([np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0]),
np.array([0.35, 0.0])
])
Delta = np.array([np.array([0.07, 0.0]),
np.array([0.07, 0.0]),
np.array([0.175, 0.0]),
np.array([0.175, 0.0]),
np.array([0.175, 0.0]),
np.array([0.175, 0.0])
])
modality_names = np.array(['Aphoton', 'Aproton'])
configurations['Alpha'] = Alpha
configurations['Beta'] = Beta
configurations['Gamma'] = Gamma
configurations['Delta'] = Delta
configurations['modality_names'] = modality_names
return configurations
#MMORT
configurations['Experiment_1'] = experiment_1()
#IMRT experiments with different target dose
configurations['Experiment_2'] = experiment_2(44.0, 81.0/44.0)
configurations['Experiment_3'] = experiment_2(44.0, 85.0/44.0)
configurations['Experiment_4'] = experiment_2(44.0, 60.0/44.0)
configurations['Experiment_5'] = experiment_2(44.0, 100.0/44.0)
#Try breaking the uniform dose:
configurations['Experiment_6'] = experiment_2(44.0, 150.0/44.0)
#Experiment with tumor max dose (tmd)
configurations['tmd_experiment_1'] = experiment_tmd()
#IMRT experiment with tumor max dose (tmd)
configurations['tmd_imrt_experiment_1'] = experiment_tmd_imrt(44.0, 81.0/44.0)
################################################
#Experiments with u_max:
configurations['mmort_photon_u_max'] = experiment_1()
#IMRT with photon
configurations['IMRT_photon_u_max'] = experiment_2(44.0, 81.0/44.0)
#IMRT with proton
configurations['IMRT_proton_u_max'] = experiment_3(44.0, 81.0/44.0)
####################################################### | 34.912568 | 121 | 0.54406 | 857 | 6,389 | 3.992999 | 0.086348 | 0.161601 | 0.140269 | 0.070134 | 0.831677 | 0.777615 | 0.758621 | 0.734366 | 0.692285 | 0.692285 | 0 | 0.102559 | 0.278134 | 6,389 | 183 | 122 | 34.912568 | 0.639419 | 0.152763 | 0 | 0.818182 | 0 | 0 | 0.075185 | 0.003987 | 0 | 0 | 0 | 0 | 0 | 1 | 0.037879 | false | 0 | 0.007576 | 0 | 0.083333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
59c0325dbf053b69b338a68d572bb7c38cd6a59e | 25 | py | Python | turnovertools/adapters/__init__.py | morganwl/turnovertools | ea911853033ed5087b40852b5adc3b8f5d0a903d | [
"MIT"
] | null | null | null | turnovertools/adapters/__init__.py | morganwl/turnovertools | ea911853033ed5087b40852b5adc3b8f5d0a903d | [
"MIT"
] | 3 | 2021-03-22T00:44:24.000Z | 2021-06-26T19:32:31.000Z | turnovertools/adapters/__init__.py | morganwl/turnovertools | ea911853033ed5087b40852b5adc3b8f5d0a903d | [
"MIT"
] | null | null | null | from .ale import AvidLog
| 12.5 | 24 | 0.8 | 4 | 25 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.16 | 25 | 1 | 25 | 25 | 0.952381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
59d781843ccc6ec5389acb8a46d4423b5faa12df | 31 | py | Python | gnsentiment/__init__.py | lufergonn/gnsentiment | ffac0b03f9e3751b972885c72ae2dd8c71403eff | [
"MIT"
] | null | null | null | gnsentiment/__init__.py | lufergonn/gnsentiment | ffac0b03f9e3751b972885c72ae2dd8c71403eff | [
"MIT"
] | null | null | null | gnsentiment/__init__.py | lufergonn/gnsentiment | ffac0b03f9e3751b972885c72ae2dd8c71403eff | [
"MIT"
] | null | null | null | from gnsentiment.core import *
| 15.5 | 30 | 0.806452 | 4 | 31 | 6.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.129032 | 31 | 1 | 31 | 31 | 0.925926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
ab895c78e258d364a473b9886b12ff92728935f8 | 139 | py | Python | common/__init__.py | ml4ai/tomcat-network-latency-test | be920be19e4e104a99f8fb4464173a3eb2540f89 | [
"MIT"
] | null | null | null | common/__init__.py | ml4ai/tomcat-network-latency-test | be920be19e4e104a99f8fb4464173a3eb2540f89 | [
"MIT"
] | null | null | null | common/__init__.py | ml4ai/tomcat-network-latency-test | be920be19e4e104a99f8fb4464173a3eb2540f89 | [
"MIT"
] | null | null | null | from .get_terminal_command import get_terminal_command
from .notify_ready import notify_ready
from .wait_for_server import wait_for_server
| 34.75 | 54 | 0.892086 | 22 | 139 | 5.181818 | 0.454545 | 0.192982 | 0.315789 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.086331 | 139 | 3 | 55 | 46.333333 | 0.897638 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
abbd99de00d74356172efb6f6c8d26c1ba416a7d | 7,433 | py | Python | tests/unit/dht/test_contact.py | ttkopec/lbry | 03415415ed397730e6f691f527f51b429a834ed5 | [
"MIT"
] | null | null | null | tests/unit/dht/test_contact.py | ttkopec/lbry | 03415415ed397730e6f691f527f51b429a834ed5 | [
"MIT"
] | 110 | 2018-11-26T05:41:35.000Z | 2021-08-03T15:37:20.000Z | tests/unit/dht/test_contact.py | ttkopec/lbry | 03415415ed397730e6f691f527f51b429a834ed5 | [
"MIT"
] | 1 | 2018-09-20T22:15:59.000Z | 2018-09-20T22:15:59.000Z | from binascii import hexlify
from twisted.internet import task
from twisted.trial import unittest
from lbrynet.core.utils import generate_id
from lbrynet.dht.contact import ContactManager
from lbrynet.dht import constants
class ContactTest(unittest.TestCase):
""" Basic tests case for boolean operators on the Contact class """
def setUp(self):
self.contact_manager = ContactManager()
self.node_ids = [generate_id(), generate_id(), generate_id()]
make_contact = self.contact_manager.make_contact
self.first_contact = make_contact(self.node_ids[1], '127.0.0.1', 1000, None, 1)
self.second_contact = make_contact(self.node_ids[0], '192.168.0.1', 1000, None, 32)
self.second_contact_second_reference = make_contact(self.node_ids[0], '192.168.0.1', 1000, None, 32)
self.first_contact_different_values = make_contact(self.node_ids[1], '192.168.1.20', 1000, None, 50)
def test_make_contact_error_cases(self):
self.assertRaises(
ValueError, self.contact_manager.make_contact, self.node_ids[1], '192.168.1.20', 100000, None)
self.assertRaises(
ValueError, self.contact_manager.make_contact, self.node_ids[1], '192.168.1.20.1', 1000, None)
self.assertRaises(
ValueError, self.contact_manager.make_contact, self.node_ids[1], 'this is not an ip', 1000, None)
self.assertRaises(
ValueError, self.contact_manager.make_contact, b'not valid node id', '192.168.1.20.1', 1000, None)
def test_no_duplicate_contact_objects(self):
self.assertTrue(self.second_contact is self.second_contact_second_reference)
self.assertTrue(self.first_contact is not self.first_contact_different_values)
def test_boolean(self):
""" Test "equals" and "not equals" comparisons """
self.assertNotEqual(
self.first_contact, self.contact_manager.make_contact(
self.first_contact.id, self.first_contact.address, self.first_contact.port + 1, None, 32
)
)
self.assertNotEqual(
self.first_contact, self.contact_manager.make_contact(
self.first_contact.id, '193.168.1.1', self.first_contact.port, None, 32
)
)
self.assertNotEqual(
self.first_contact, self.contact_manager.make_contact(
generate_id(), self.first_contact.address, self.first_contact.port, None, 32
)
)
self.assertEqual(self.second_contact, self.second_contact_second_reference)
def test_compact_ip(self):
self.assertEqual(self.first_contact.compact_ip(), b'\x7f\x00\x00\x01')
self.assertEqual(self.second_contact.compact_ip(), b'\xc0\xa8\x00\x01')
def test_id_log(self):
self.assertEqual(self.first_contact.log_id(False), hexlify(self.node_ids[1]))
self.assertEqual(self.first_contact.log_id(True), hexlify(self.node_ids[1])[:8])
class TestContactLastReplied(unittest.TestCase):
def setUp(self):
self.clock = task.Clock()
self.contact_manager = ContactManager(self.clock.seconds)
self.contact = self.contact_manager.make_contact(generate_id(), "127.0.0.1", 4444, None)
self.clock.advance(3600)
self.assertTrue(self.contact.contact_is_good is None)
def test_stale_replied_to_us(self):
self.contact.update_last_replied()
self.assertTrue(self.contact.contact_is_good is True)
def test_stale_requested_from_us(self):
self.contact.update_last_requested()
self.assertTrue(self.contact.contact_is_good is None)
def test_stale_then_fail(self):
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is None)
self.clock.advance(1)
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is False)
def test_good_turned_stale(self):
self.contact.update_last_replied()
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(constants.checkRefreshInterval - 1)
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is None)
def test_good_then_fail(self):
self.contact.update_last_replied()
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(59)
self.assertTrue(self.contact.contact_is_good is True)
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is False)
for _ in range(7200):
self.clock.advance(60)
self.assertTrue(self.contact.contact_is_good is False)
def test_good_then_fail_then_good(self):
# it replies
self.contact.update_last_replied()
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
# it fails twice in a row
self.contact.update_last_failed()
self.clock.advance(1)
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is False)
self.clock.advance(1)
# it replies
self.contact.update_last_replied()
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is True)
# it goes stale
self.clock.advance(constants.checkRefreshInterval - 2)
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is None)
class TestContactLastRequested(unittest.TestCase):
def setUp(self):
self.clock = task.Clock()
self.contact_manager = ContactManager(self.clock.seconds)
self.contact = self.contact_manager.make_contact(generate_id(), "127.0.0.1", 4444, None)
self.clock.advance(1)
self.contact.update_last_replied()
self.clock.advance(3600)
self.assertTrue(self.contact.contact_is_good is None)
def test_previous_replied_then_requested(self):
# it requests
self.contact.update_last_requested()
self.assertTrue(self.contact.contact_is_good is True)
# it goes stale
self.clock.advance(constants.checkRefreshInterval - 1)
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is None)
def test_previous_replied_then_requested_then_failed(self):
# it requests
self.contact.update_last_requested()
self.assertTrue(self.contact.contact_is_good is True)
self.clock.advance(1)
# it fails twice in a row
self.contact.update_last_failed()
self.clock.advance(1)
self.contact.update_last_failed()
self.assertTrue(self.contact.contact_is_good is False)
self.clock.advance(1)
# it requests
self.contact.update_last_requested()
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is False)
# it goes stale
self.clock.advance((constants.refreshTimeout / 4) - 2)
self.assertTrue(self.contact.contact_is_good is False)
self.clock.advance(1)
self.assertTrue(self.contact.contact_is_good is False)
| 42.232955 | 110 | 0.690031 | 993 | 7,433 | 4.944612 | 0.123867 | 0.13442 | 0.106314 | 0.137475 | 0.828106 | 0.767821 | 0.752138 | 0.71609 | 0.696334 | 0.662118 | 0 | 0.033186 | 0.209471 | 7,433 | 175 | 111 | 42.474286 | 0.802417 | 0.034037 | 0 | 0.605839 | 1 | 0 | 0.024867 | 0 | 0 | 0 | 0 | 0 | 0.29927 | 1 | 0.116788 | false | 0 | 0.043796 | 0 | 0.182482 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
abc3e285dcf9fc26baedb9ce3340a53ba4356c38 | 22 | py | Python | avalanche/benchmarks/datasets/cub200/__init__.py | PRISHIta123/avalanche | cf92e4e1b7135fedd04106a195eb1fb67b97c124 | [
"MIT"
] | 810 | 2018-10-08T15:49:05.000Z | 2022-03-31T15:28:09.000Z | avalanche/benchmarks/datasets/cub200/__init__.py | PRISHIta123/avalanche | cf92e4e1b7135fedd04106a195eb1fb67b97c124 | [
"MIT"
] | 477 | 2021-03-01T17:50:51.000Z | 2022-03-31T14:51:23.000Z | avalanche/benchmarks/datasets/cub200/__init__.py | PRISHIta123/avalanche | cf92e4e1b7135fedd04106a195eb1fb67b97c124 | [
"MIT"
] | 147 | 2018-10-08T15:49:18.000Z | 2022-03-31T04:08:45.000Z | from .cub200 import *
| 11 | 21 | 0.727273 | 3 | 22 | 5.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 0.181818 | 22 | 1 | 22 | 22 | 0.722222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
e61856fd757b7ea554e3b0e5f633a65035c6142d | 29 | py | Python | evoke/Page/__init__.py | howiemac/evoke5 | 430d6dfd719f8c88a4c3de2b735f8736187ff19b | [
"BSD-3-Clause"
] | null | null | null | evoke/Page/__init__.py | howiemac/evoke5 | 430d6dfd719f8c88a4c3de2b735f8736187ff19b | [
"BSD-3-Clause"
] | null | null | null | evoke/Page/__init__.py | howiemac/evoke5 | 430d6dfd719f8c88a4c3de2b735f8736187ff19b | [
"BSD-3-Clause"
] | null | null | null | from .Page import Page, html
| 14.5 | 28 | 0.758621 | 5 | 29 | 4.4 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.172414 | 29 | 1 | 29 | 29 | 0.916667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
e6485ad5e01a389e30e50965ab2bc06d6e8097b3 | 4,075 | py | Python | deepclean_prod/nn/net.py | trivnguyen/deepclean_prod | f724508c0b2f1d7ff3106f55ae3a468547ab85c6 | [
"MIT"
] | null | null | null | deepclean_prod/nn/net.py | trivnguyen/deepclean_prod | f724508c0b2f1d7ff3106f55ae3a468547ab85c6 | [
"MIT"
] | null | null | null | deepclean_prod/nn/net.py | trivnguyen/deepclean_prod | f724508c0b2f1d7ff3106f55ae3a468547ab85c6 | [
"MIT"
] | 1 | 2021-11-03T10:15:58.000Z | 2021-11-03T10:15:58.000Z |
import torch.nn as nn
# class DeepClean(nn.Module):
# def __init__(self, in_channels):
# super().__init__()
# self.input_conv = nn.Sequential(
# nn.Conv1d(in_channels, in_channels, kernel_size=7, stride=1, padding=3),
# nn.BatchNorm1d(in_channels),
# nn.Tanh()
# )
# self.downsampler = nn.Sequential()
# self.downsampler.add_module('CONV_1', nn.Conv1d(in_channels, 8, kernel_size=7, stride=2, padding=3))
# self.downsampler.add_module('BN_1', nn.BatchNorm1d(8))
# self.downsampler.add_module('TANH_1', nn.Tanh())
# self.downsampler.add_module('CONV_2', nn.Conv1d(8, 16, kernel_size=7, stride=2, padding=3))
# self.downsampler.add_module('BN_2', nn.BatchNorm1d(16))
# self.downsampler.add_module('TANH_2', nn.Tanh())
# self.downsampler.add_module('CONV_3', nn.Conv1d(16, 32, kernel_size=7, stride=2, padding=3))
# self.downsampler.add_module('BN_3', nn.BatchNorm1d(32))
# self.downsampler.add_module('TANH_3', nn.Tanh())
# self.downsampler.add_module('CONV_4', nn.Conv1d(32, 64, kernel_size=7, stride=2, padding=3))
# self.downsampler.add_module('BN_4', nn.BatchNorm1d(64))
# self.downsampler.add_module('TANH_4', nn.Tanh())
# self.upsampler = nn.Sequential()
# self.upsampler.add_module(
# 'CONVTRANS_1', nn.ConvTranspose1d(64, 32, kernel_size=7, stride=2, padding=3, output_padding=1))
# self.upsampler.add_module('BN_1', nn.BatchNorm1d(32))
# self.upsampler.add_module('TANH_1', nn.Tanh())
# self.upsampler.add_module(
# 'CONVTRANS_2', nn.ConvTranspose1d(32, 16, kernel_size=7, stride=2, padding=3, output_padding=1))
# self.upsampler.add_module('BN_2', nn.BatchNorm1d(16))
# self.upsampler.add_module('TANH_2', nn.Tanh())
# self.upsampler.add_module(
# 'CONVTRANS_3', nn.ConvTranspose1d(16, 8, kernel_size=7, stride=2, padding=3, output_padding=1))
# self.upsampler.add_module('BN_3', nn.BatchNorm1d(8))
# self.upsampler.add_module('TANH_3', nn.Tanh())
# self.upsampler.add_module(
# 'CONVTRANS_4', nn.ConvTranspose1d(8,in_channels, kernel_size=7, stride=2, padding=3, output_padding=1))
# self.upsampler.add_module('BN_4', nn.BatchNorm1d(in_channels))
# self.upsampler.add_module('TANH_4', nn.Tanh())
# self.output_conv = nn.Conv1d(in_channels, 1, kernel_size=7, stride=1, padding=3)
# def forward(self, x):
# x = self.input_conv(x)
# x = self.downsampler(x)
# x = self.upsampler(x)
# x = self.output_conv(x)
# x = x.view(x.shape[0], -1)
# return x
class DeepClean(nn.Module):
def __init__(self, in_channels):
super().__init__()
self.input_conv = nn.Sequential(
nn.Conv1d(in_channels, in_channels, kernel_size=7, stride=1, padding=3),
# nn.BatchNorm1d(in_channels),
# nn.Tanh()
)
self.downsampler = nn.Sequential()
self.downsampler.add_module('CONV_1', nn.Conv1d(in_channels, 8, kernel_size=7, stride=2, padding=3))
# self.downsampler.add_module('BN_1', nn.BatchNorm1d(8))
# self.downsampler.add_module('TANH_1', nn.Tanh())
self.upsampler = nn.Sequential()
self.upsampler.add_module(
'CONVTRANS_1', nn.ConvTranspose1d(8, in_channels, kernel_size=7, stride=2, padding=3, output_padding=1))
# self.upsampler.add_module('BN_1', nn.BatchNorm1d(in_channels))
# self.upsampler.add_module('TANH_1', nn.Tanh())
self.output_conv = nn.Conv1d(in_channels, 1, kernel_size=7, stride=1, padding=3)
def forward(self, x):
x = self.input_conv(x)
x = self.downsampler(x)
x = self.upsampler(x)
x = self.output_conv(x)
x = x.view(x.shape[0], -1)
return x
| 45.786517 | 117 | 0.604908 | 544 | 4,075 | 4.3125 | 0.082721 | 0.11509 | 0.11509 | 0.153453 | 0.956948 | 0.930094 | 0.911765 | 0.803069 | 0.778346 | 0.725916 | 0 | 0.048177 | 0.246135 | 4,075 | 89 | 118 | 45.786517 | 0.715495 | 0.718282 | 0 | 0 | 0 | 0 | 0.015525 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0.05 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
e65fbf90e6316ba92da1d713fa631aef56361bc6 | 98 | py | Python | tests/test_importable.py | jack1142/quickpython | 96ab4db027138db2c5babf41988f3782336b9135 | [
"MIT"
] | 115 | 2020-08-17T06:39:43.000Z | 2022-01-24T16:09:53.000Z | tests/test_importable.py | jack1142/quickpython | 96ab4db027138db2c5babf41988f3782336b9135 | [
"MIT"
] | 5 | 2020-11-21T10:42:02.000Z | 2021-03-07T09:29:26.000Z | tests/test_importable.py | jack1142/quickpython | 96ab4db027138db2c5babf41988f3782336b9135 | [
"MIT"
] | 5 | 2020-11-21T18:04:18.000Z | 2021-03-06T17:49:45.000Z | """A basic import test"""
def test_can_import():
import quickpython
assert quickpython
| 12.25 | 25 | 0.693878 | 12 | 98 | 5.5 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.214286 | 98 | 7 | 26 | 14 | 0.857143 | 0.193878 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0.333333 | true | 0 | 0.666667 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
054bdc29009123da92f9bfe74ba407fbd13a0770 | 33 | py | Python | app/component/__init__.py | Nathanlauga/football-python-flask-app | 65e6ad31140514646342033dc5227be254fb998e | [
"MIT"
] | 1 | 2021-01-02T07:16:53.000Z | 2021-01-02T07:16:53.000Z | app/component/__init__.py | laelasbuch/football-python-flask-app | 65e6ad31140514646342033dc5227be254fb998e | [
"MIT"
] | 1 | 2021-06-02T00:40:37.000Z | 2021-06-02T00:40:37.000Z | app/component/__init__.py | laelasbuch/football-python-flask-app | 65e6ad31140514646342033dc5227be254fb998e | [
"MIT"
] | 5 | 2019-11-16T09:21:30.000Z | 2022-02-12T15:36:39.000Z | from .component import IndexForm
| 16.5 | 32 | 0.848485 | 4 | 33 | 7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121212 | 33 | 1 | 33 | 33 | 0.965517 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
552945305d6141c9851dd8bc7647050a8db9b62e | 89 | py | Python | src/road_collisions_us/__init__.py | RobertLucey/road-collisions-us | 8d1be0d4e3519dbd922721c0b751bd992871e41d | [
"Unlicense"
] | null | null | null | src/road_collisions_us/__init__.py | RobertLucey/road-collisions-us | 8d1be0d4e3519dbd922721c0b751bd992871e41d | [
"Unlicense"
] | null | null | null | src/road_collisions_us/__init__.py | RobertLucey/road-collisions-us | 8d1be0d4e3519dbd922721c0b751bd992871e41d | [
"Unlicense"
] | null | null | null | from road_collisions_us.download import ensure_data_downloaded
ensure_data_downloaded()
| 22.25 | 62 | 0.898876 | 12 | 89 | 6.166667 | 0.75 | 0.27027 | 0.540541 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.067416 | 89 | 3 | 63 | 29.666667 | 0.891566 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
55344226189294de8d24b2ce036430db359401a4 | 21,597 | py | Python | First Game.py | mdn117/First-Game | 45e5948b4770226f64dbd847d25a6a207f12b8f9 | [
"Apache-2.0"
] | null | null | null | First Game.py | mdn117/First-Game | 45e5948b4770226f64dbd847d25a6a207f12b8f9 | [
"Apache-2.0"
] | null | null | null | First Game.py | mdn117/First-Game | 45e5948b4770226f64dbd847d25a6a207f12b8f9 | [
"Apache-2.0"
] | null | null | null | #First Game: by Matthew Nicholson
#Date last modified: 4/17/19 at 6:26 PM
import pygame
from math import floor
import os
pygame.init()
screen_width = 1080 #width and height are standard resolution sizes for HD
screen_height = 720
win = pygame.display.set_mode((screen_width, screen_height)) #sets the dimensions of the screen
pygame.display.set_caption("First Game")
bg = pygame.transform.scale((pygame.image.load('background.png')), (screen_width * 2, screen_height * 2)) #loads the background
idle = pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-00.png'))
clock = pygame.time.Clock()
class player(object):
def __init__(self, x, y, width, height):
self.x = x #the players horizontal position
self.y = y #the players vertical position
self.width = width #the players horizontal size
self.height = height #the players vertical size
self.vel = 25 #the speed of the player when moving
self.isJump = False #set to true if the player presses the jump button
self.jumpCount = 10
self.left = False #set to true if player is moving left
self.right = False #set to true if the player is moving right
self.idle = True #set to false if the player moves or jumps or attacks
self.didAttack = False #set to true if the player uses the attack button
self.didJumpAndAttack = False #set to true if the player jumps then attacks
self.attackDone = False #set to true if the attack animation finishes
self.jumpAttackDone = False #set to true if the jump attack animation finishes
self.walkCount = 0
self.idleCount = 0
self.jumpIter = 0
self.attackIter = 0
self.jumpAttackIter = 0
#from self.walkRight to self.leftAttack,
#these are all of the sprite animations
#for the player, each as a list that is
#iterated through the main loop
self.walkRight = [pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-03.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-04.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-05.png'))), (self.width, self.height))]
self.walkLeft = [pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-03.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-04.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-run-05.png'))), True, False)), (self.width, self.height))]
self.rightIdle = [pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-03.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-03.png'))), (self.width, self.height))]
self.leftIdle = [pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-03.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-idle-2-03.png'))), True, False)), (self.width, self.height))]
self.rightJump = [pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-03.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-03.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-01.png'))), (self.width, self.height))]
self.leftJump = [pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-03.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-jump-03.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-fall-01.png'))), True, False)), (self.width, self.height))]
self.rightAttack = [pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-03.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-04.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-05.png'))), (self.width, self.height))]
self.leftAttack = [pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-03.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-04.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-attack2-05.png'))), True, False)), (self.width, self.height))]
self.rightAirAttack = [pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-00.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-01.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-02.png'))), (self.width, self.height)),
pygame.transform.scale((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-03.png'))), (self.width, self.height))]
self.leftAirAttack = [pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-00.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-01.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-02.png'))), True, False)), (self.width, self.height)),
pygame.transform.scale((pygame.transform.flip((pygame.image.load(os.path.join('Protagonist animation', 'adventurer-air-attack1-03.png'))), True, False)), (self.width, self.height))]
def draw(self, win):
if self.walkCount + 1 >= 24:
self.walkCount = 0
if self.idleCount + 1 >= 64:
self.idleCount = 0
if self.jumpIter + 1 >= 40:
self.jumpIter = 0
if self.attackIter + 1 >= 8:
self.attackDone = True
self.attackIter = 0
self.idleCount = 40
self.walkCount = 0
if self.jumpAttackIter +1 >= 8:
self.jumpAttackDone = True
self.jumpAttackIter = 0
if not(self.idle):
if self.left:
if self.isJump:
if self.didJumpAndAttack:
if not(self.jumpAttackDone):
win.blit(self.leftAirAttack[self.jumpAttackIter//2], (self.x,self.y))
self.jumpAttackIter += 1
else:
win.blit(self.leftJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
win.blit(self.leftJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
if self.didAttack and not(self.attackDone):
win.blit(self.leftAttack[self.attackIter//2], (self.x,self.y))
self.attackIter += 1
else:
win.blit(self.walkLeft[self.walkCount//4], (self.x,self.y))
self.walkCount += 1
elif self.right:
if self.isJump:
if self.didJumpAndAttack:
if not(self.jumpAttackDone):
win.blit(self.rightAirAttack[self.jumpAttackIter//2], (self.x,self.y))
self.jumpAttackIter += 1
else:
win.blit(self.rightJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
win.blit(self.rightJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
if self.didAttack and not(self.attackDone):
win.blit(self.rightAttack[self.attackIter//2], (self.x,self.y))
self.attackIter += 1
else:
win.blit(self.walkRight[self.walkCount//4], (self.x,self.y))
self.walkCount += 1
else:
if self.didAttack and not(self.attackDone):
if self.left:
win.blit(self.leftAttack[self.attackIter//2], (self.x,self.y))
self.attackIter += 1
else: #self.right
win.blit(self.rightAttack[self.attackIter//2], (self.x,self.y))
self.attackIter += 1
elif self.isJump:
if self.left:
if self.didJumpAndAttack:
if not(self.jumpAttackDone):
win.blit(self.leftAirAttack[self.jumpAttackIter//2], (self.x,self.y))
self.jumpAttackIter += 1
else:
win.blit(self.leftJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
win.blit(self.leftJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else: #self.right
if self.didJumpAndAttack:
if not(self.jumpAttackDone):
win.blit(self.rightAirAttack[self.jumpAttackIter//2], (self.x,self.y))
self.jumpAttackIter += 1
else:
win.blit(self.rightJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
else:
win.blit(self.rightJump[self.jumpIter//4], (self.x,self.y))
self.jumpIter += 1
elif self.left:
win.blit(self.leftIdle[self.idleCount//8], (self.x,self.y))
self.idleCount += 1
else: #self.right
win.blit(self.rightIdle[self.idleCount//8], (self.x,self.y))
self.idleCount += 1
class enemy(object):
def __init__(self, x, y, width, height):
self.x = x
self.y = y
self.width = width
self.height = height
self.idle = pygame.transform.scale((pygame.image.load(os.path.join('Slime animation', 'slime-idle-0.png'))), (self.width, self.height))
def draw (self, win):
win.blit(self.idle, (self.x,self.y))
def redrawGameWindow():
win.blit(bg,(0,floor(-((25/27) * screen_height))))
man.draw(win)
slime.draw(win)
pygame.display.update()
#main loop
man = player(((1/96) * screen_width), ((20/27) * screen_height), floor(((5/32) * screen_width)), floor(((37/180) * screen_height)))
slime = enemy(1400, 875, 192, 150)
run = True
while run:
clock.tick(60)
for event in pygame.event.get():
if event.type == pygame.QUIT:
run = False
keys = pygame.key.get_pressed()
if keys[pygame.K_LEFT] and man.x > man.vel:
if man.didAttack and not(man.attackDone):
man.walkCount = 0
else:
man.x -= man.vel
man.left = True
man.right = False
man.idle = False
elif keys[pygame.K_RIGHT] and man.x < screen_width - man.width - man.vel:
if man.didAttack and not(man.attackDone):
man.walkCount = 0
else:
man.x += man.vel
man.right = True
man.left = False
man.idle = False
else:
man.idle = True
man.walkCount = 0
if not(man.isJump):
if keys[pygame.K_UP]:
man.isJump = True
else:
if not(man.didJumpAndAttack):
if keys[pygame.K_SPACE] and keys[pygame.K_LEFT] and man.x > man.vel:
man.left = True
man.right = False
man.didJumpAndAttack = True
man.jumpAttackDone = False
elif keys[pygame.K_SPACE] and keys[pygame.K_RIGHT] and man.x < screen_width - man.width - man.vel:
man.right = True
man.left = False
man.didJumpAndAttack = True
man.jumpAttackDone = False
elif keys[pygame.K_SPACE] and (not(keys[pygame.K_LEFT]) or not(keys[pygame.K_RIGHT])):
man.didJumpAndAttack = True
man.jumpAttackDone = False
else:
if man.jumpAttackDone:
man.didJumpAndAttack = False
man.didAttack = False
else:
man.didAttack = False
if man.jumpCount >= -10:
neg = 1
if man.jumpCount < 0:
neg = -1
man.y -= (man.jumpCount ** 2) * 0.5 * neg
man.jumpCount -= 1
else:
man.isJump = False
man.didJumpAndAttack = False
man.jumpAttackDone = True
man.jumpCount = 10
if not(man.didAttack):
if keys[pygame.K_SPACE]:
man.didAttack = True
man.attackDone = False
else:
if man.attackDone:
man.didAttack = False
redrawGameWindow()
pygame.quit()
| 70.348534 | 212 | 0.584989 | 2,514 | 21,597 | 5.011535 | 0.07319 | 0.116676 | 0.079768 | 0.136201 | 0.814192 | 0.803476 | 0.793793 | 0.775935 | 0.765616 | 0.747282 | 0 | 0.018452 | 0.26976 | 21,597 | 306 | 213 | 70.578431 | 0.78042 | 0.040283 | 0 | 0.501832 | 0 | 0 | 0.143859 | 0.074234 | 0 | 0 | 0 | 0 | 0 | 1 | 0.018315 | false | 0 | 0.010989 | 0 | 0.03663 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
5575a65a974c2d9197bc107c3b92dc2f9873f84d | 65 | py | Python | nhlscraperpy/scrapers/game.py | mvais/nhlscraperpy | 5f7b72ea165f258ed19fcdc597a2ba8047dcd47e | [
"MIT"
] | null | null | null | nhlscraperpy/scrapers/game.py | mvais/nhlscraperpy | 5f7b72ea165f258ed19fcdc597a2ba8047dcd47e | [
"MIT"
] | null | null | null | nhlscraperpy/scrapers/game.py | mvais/nhlscraperpy | 5f7b72ea165f258ed19fcdc597a2ba8047dcd47e | [
"MIT"
] | null | null | null | from bs4 import BeautifulSoup
def scrape_game(id):
return None | 16.25 | 29 | 0.8 | 10 | 65 | 5.1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018182 | 0.153846 | 65 | 4 | 30 | 16.25 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0.333333 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 6 |
5583a70dcea9c24cc1d070111ee28211ea175b96 | 43 | py | Python | xdl/platforms/modular_wheel/__init__.py | mcrav/xdl | c120a1cf50a9b668a79b118700930eb3d60a9298 | [
"MIT"
] | null | null | null | xdl/platforms/modular_wheel/__init__.py | mcrav/xdl | c120a1cf50a9b668a79b118700930eb3d60a9298 | [
"MIT"
] | null | null | null | xdl/platforms/modular_wheel/__init__.py | mcrav/xdl | c120a1cf50a9b668a79b118700930eb3d60a9298 | [
"MIT"
] | null | null | null | from .platform import ModularWheelPlatform
| 21.5 | 42 | 0.883721 | 4 | 43 | 9.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.093023 | 43 | 1 | 43 | 43 | 0.974359 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
559dbe3d5cc1dd349b159bebb757f512a4cd056a | 92 | py | Python | CodeWars/7 Kyu/Slope of a Line.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | CodeWars/7 Kyu/Slope of a Line.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | CodeWars/7 Kyu/Slope of a Line.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | def getSlope(p1, p2):
return None if p1[0] == p2[0] else (p2[1] - p1[1])/(p2[0] - p1[0]) | 46 | 70 | 0.532609 | 20 | 92 | 2.45 | 0.5 | 0.122449 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.189189 | 0.195652 | 92 | 2 | 70 | 46 | 0.472973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0.5 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
e9ceb1d9e15f1d0ff4185aaa98e0bac31612ebe5 | 146 | py | Python | accounts/models.py | powerticket/heroku | d214a3758efbf185e4a533f8373033ed558209dd | [
"MIT"
] | null | null | null | accounts/models.py | powerticket/heroku | d214a3758efbf185e4a533f8373033ed558209dd | [
"MIT"
] | 4 | 2020-10-20T15:13:32.000Z | 2021-02-24T09:04:49.000Z | accounts/models.py | powerticket/heroku | d214a3758efbf185e4a533f8373033ed558209dd | [
"MIT"
] | null | null | null | from django.contrib.auth.models import AbstractUser
from django.db import models
# Create your models here.
class MyUser(AbstractUser):
pass | 20.857143 | 51 | 0.794521 | 20 | 146 | 5.8 | 0.7 | 0.172414 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.143836 | 146 | 7 | 52 | 20.857143 | 0.928 | 0.164384 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.25 | 0.5 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 6 |
7567fdb6856974e52c74a8d1b6ba40150d784fdd | 74,405 | py | Python | venv/Model/ReportModule.py | florianbeyer/maptor | 8fd899dd3123484fd83b7aa74a007edc8879dba6 | [
"MIT"
] | 1 | 2022-03-15T13:35:26.000Z | 2022-03-15T13:35:26.000Z | venv/Model/ReportModule.py | florianbeyer/maptor | 8fd899dd3123484fd83b7aa74a007edc8879dba6 | [
"MIT"
] | 9 | 2021-01-30T16:55:50.000Z | 2022-03-12T00:54:37.000Z | venv/Model/ReportModule.py | florianbeyer/maptor | 8fd899dd3123484fd83b7aa74a007edc8879dba6 | [
"MIT"
] | 1 | 2020-12-21T02:24:46.000Z | 2020-12-21T02:24:46.000Z | try:
import sys,logging
from reportlab.pdfgen import canvas
from reportlab.platypus import Table,TableStyle
from reportlab.lib import colors
from reportlab.lib.pagesizes import A4
from reportlab.graphics import renderPDF
from svglib.svglib import svg2rlg
from io import BytesIO
from datetime import date
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
from reportlab.platypus.tables import Table
import seaborn as sns
import os
import pandas as pd
from sklearn.cross_decomposition import PLSRegression
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import cross_val_predict
from sklearn import preprocessing
# sys.path.append(r"F:\Work\Maptor\venv\HelpingModel")
from PLSR_SSS_Helper import PLSR_SSS_Helper
from RFHelper import RFHelper
from osgeo import gdal, ogr, gdal_array # I/O image data
import numpy as np # math and array handling
import matplotlib.pyplot as plt # plot figures
import pandas as pd # handling large data as table sheets
from joblib import dump, load
from operator import itemgetter
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import cross_val_predict
except Exception as e:
print('Can not import files:' + str(e))
input("Press Enter to exit!")
sys.exit(0)
class ReportModule():
def build_doc(self,path,mode):
try:
doc = canvas.Canvas(path)
doc.setLineWidth(.3)
doc.setFont('Helvetica-Bold', 16)
doc.drawString(30, 810, mode)
doc.setFont('Helvetica', 12)
doc.drawString(30, 793, 'Software Maptor v1.4')
doc.drawString(30, 779, "Developer: Florian Beyer & Qasim Usmani")
doc.drawString(30, 765, 'Support: florian.beyer@uni-rostock.de')
today = date.today()
doc.drawString(30, 751, "Date: " + str(today))
doc.drawString(30, 737, '')
doc.line(20, 735, 570, 735)
return doc
except ValueError as e:
logging.error("Exception occurred", exc_info=True)
print(e)
def Clf_prepare_report(self,doc,img,roi,importance,table_M,trees,ob_score,class_prediction,ValidationData,attribute,dir_path):
try:
os.mkdir(dir_path+"/Graphs")
path = dir_path + "/Graphs/"
fig = plt.figure(figsize=(6, 6))
plt.subplot(221)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
plt.title('RS Image - first band')
plt.subplot(222)
plt.imshow(class_prediction, cmap=plt.cm.Spectral)
plt.title('Classification result')
plt.subplot(223)
plt.imshow(roi, cmap=plt.cm.Spectral)
plt.title('Training Data')
plt.subplot(224)
plt.imshow(ValidationData, cmap=plt.cm.Spectral)
plt.title('Validation Data')
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 30, 210)
fig.clf()
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
plt.title('RS Image - first band')
plt.savefig(path + "'RS_Image.png", dpi=300)
plt.clf()
plt.imshow(class_prediction, cmap=plt.cm.Spectral)
plt.title('Classification result')
plt.savefig(path + "Classification_result.png", dpi=300)
plt.clf()
plt.imshow(roi, cmap=plt.cm.Spectral)
plt.title('Training Data')
plt.savefig(path + "Training_Data.png", dpi=300)
plt.clf()
plt.imshow(ValidationData, cmap=plt.cm.Spectral)
plt.title('Validation Data')
plt.savefig(path + "Validation_Data.png", dpi=300)
plt.clf()
doc.showPage()
# doc.line(20, 810, 570, 810)
# doc.setLineWidth(.3)
# doc.setFont('Helvetica-Bold', 14)
# doc.drawString(30, 790, 'Section 1: General Information and Training')
# doc.drawString(30, 770, "Section 2: Validation")
# doc.line(20, 750, 570, 750)
n_samples = (roi > 0).sum()
# doc.drawString(30, 730, "Section :1")
doc.setFont('Helvetica', 12)
doc.drawString(30, 710, 'Image Extent: ' + str(img.shape[0]) + " x " + str(img.shape[1]))
doc.drawString(30, 690, 'Number of Bands: ' + str(len(importance)))
doc.drawString(30, 670, 'Field Name (shape file) of your classes: ' + attribute)
doc.drawString(30, 650, 'Random Forest Training: ')
doc.drawString(30, 630, 'Number of Trees: ' + str(trees))
doc.drawString(30, 610, 'Number of training Pixel: ' + str(n_samples))
# What are our classification labels?
labels = np.unique(roi[roi > 0])
# print('Number of classes :'+ labels.size)
doc.drawString(30, 590, 'Number of classes :' + str(labels.size))
doc.drawString(30, 570, 'Out-Of-Bag prediction of accuracy: ' + str(ob_score))
# doc.showPage()
X = img[roi > 0, :]
y = roi[roi > 0]
data = ["Band","Importance"]
data= [(k, v) for k, v in importance.items()]
data2 = data[:]
# dummy = [['00', '01'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['00', '01'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['00', '01'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['00', '01'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21'],
# ['10', '11'],
# ['20', '21'],
# ['30', '31'],
# ['20', '21'],
# ['20', '21'],
# ['20', '21']]
#
# data.extend(dummy)
data2.sort(key=lambda x: x[1], reverse=True)
data.insert(0, ("Band", "Importance"))
data2.insert(0, ("Band", "Importance"))
fig = plt.figure(figsize=(6, 6))
sns.heatmap(table_M, annot=True, cmap="BuPu", fmt='g')
#plt.show()
imgdata = BytesIO()
fig.savefig(path+"pred_acc_training.png")
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30,520,"Convolution matrix (prediction accuracy of the training data):")
renderPDF.draw(drawing, doc, 30, 30)
doc.showPage()
doc.drawString(30, 700, "Band importance (left: ordered by band number | right: ordered by importance):")
if (len(data) > 21):
chunks = (self.chunks(data, 20))
ordered_chunks = (self.chunks(data2, 20))
iterationNumer = 0
for unorder, ordered in zip(chunks, ordered_chunks):
if iterationNumer != 0:
unorder.insert(0, ("Band", "Importance"))
ordered.insert(0, ("Band", "Importance"))
unordered_table = Table(unorder)
ordered_table = Table(ordered)
unordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
ordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
unordered_table.wrapOn(doc, 60, 200)
unordered_table.drawOn(doc, 60, 200)
ordered_table.wrapOn(doc, 280, 200)
ordered_table.drawOn(doc, 280, 200)
# else:
# unordered_table.wrapOn(doc, 60, 400)
# unordered_table.drawOn(doc, 60, 400)
#
# ordered_table.wrapOn(doc, 280, 400)
# ordered_table.drawOn(doc, 280, 400)
columns = [""]
ordered_table = Table(columns)
unordered_table = Table(columns)
doc.showPage()
iterationNumer += 1
else:
table = Table(data)
table2 = Table(data2)
table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table.wrapOn(doc, 60, 400)
table.drawOn(doc, 60, 400)
table2.wrapOn(doc, 280, 400)
table2.drawOn(doc, 280, 400)
doc.showPage()
#print(trees)
#print(table)
#print(importance)
return doc
except ValueError as e:
logging.error("Exception occurred", exc_info=True)
print(e)
def Clf_prepare_section3(self,doc,X_v,y_v,convolution_mat,df_sum_mat,score,roi_v,model_path,Image_savePath,dir_path):
try:
#print(Image_savePath+"here.................!!")
dir_path +="/Graphs/"
n_samples = (roi_v > 0).sum()
#print("Number of validation Pixels: "+ str(n_samples))
doc.setFont('Helvetica-Bold', 12)
doc.drawString(30, 780, "Number of validation Pixels: "+ str(n_samples))
doc.setFont('Helvetica-Bold', 12)
#print(score)
doc.drawString(30, 760, str(score))
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 720, "Convolution matrix (prediction accuracy of the validation data")
convolution_mat.index = convolution_mat.index.rename('truth')
convolution_mat.columns = convolution_mat.columns.rename('predict')
del convolution_mat['All']
convolution_mat = convolution_mat.drop('All', axis=0)
fig = plt.figure(figsize=(6, 5))
sns.heatmap(convolution_mat, annot=True, cmap="BuPu", fmt='g')
# plt.show()
imgdata = BytesIO()
fig.savefig(dir_path + "pred_acc_validation.png")
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 40, 300)
fig.clf()
df_sum_mat = df_sum_mat.round(3)
accuracy = df_sum_mat.iloc[-3:]
df_sum_mat = df_sum_mat.head(-3)
r, c = df_sum_mat.shape
seq = list(range(1, r+1))
df_sum_mat.insert(0,"band",seq)
data = np.array(df_sum_mat).tolist()
data.insert(0,("class","precision","recall","f1-score","support"))
t1 = Table(data)
t1.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
doc.showPage()
doc.drawString(30, 760,"Precision, recall, F-measure and support for each class:")
t1.wrapOn(doc, 30, 500)
t1.drawOn(doc, 90, 500)
# acc_col_name = ['accuracy','macro avg','weighted avg']
# accuracy.insert(0,".",acc_col_name)
# acc_data = np.array(accuracy).tolist()
# t2 = Table(acc_data)
#
# t2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
# ('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
# t2.wrapOn(doc, 30, 100)
# t2.drawOn(doc, 330, 100)
doc.setFont('Helvetica', 8)
doc.drawString(20, 370, "Image Saved to Path: "+Image_savePath)
# if model_path!="/":
# doc.drawString(30, 20, "Model Saved to Path: Model not Save")
# else:
doc.drawString(20, 350, "Model Saved to Path:"+ model_path)
return doc
except ValueError as e:
logging.error("Exception occurred", exc_info=True)
print(e)
def make_rf_reg_report(self,doc,img,RFHelper,dir_path):
# Display images
try:
os.mkdir(dir_path + "/Graphs")
path = dir_path + "/Graphs/"
width, height = A4
print("here........."+RFHelper.reportpath)
print(RFHelper.prediction_map)
print(RFHelper.modelsavepath)
print(RFHelper.img_path)
print(RFHelper.train_data)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 700,"DIRECTORIES:")
doc.setFont('Helvetica', 7)
doc.drawString(30, 680, "Remote Sensing Image: " + RFHelper.img_path)
doc.drawString(30, 660, "Shape file: " + RFHelper.train_data)
doc.drawString(30, 640, "Report Save Path: "+ RFHelper.reportpath)
doc.drawString(30, 620, "Regression image saved to: " +RFHelper.prediction_map)
if RFHelper.modelsavepath !='/':
doc.drawString(30, 600, "Model saved to: "+RFHelper.modelsavepath)
else:
doc.drawString(30, 600, "Model saved to: Model not saved")
doc.line(20, 580, 570, 580)
if img.shape[0] > img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
print(img.shape)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(RFHelper.training > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('first RS band and sample points', fontsize=8)
plt.title('RS image - first band')
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 160)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(RFHelper.prediction, cmap=plt.cm.Spectral)
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 400, 160)
fig.clf()
plt.close(fig)
doc.showPage()
if img.shape[0]<= img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
print(img.shape)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(RFHelper.training > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('first RS band and sample points', fontsize=8)
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 360)
# else:
# renderPDF.draw(drawing, doc, 50, 250)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(RFHelper.prediction, cmap=plt.cm.Spectral)
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 70, 60)
fig.clf()
plt.close(fig)
doc.showPage()
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(RFHelper.training > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('first RS band and sample points', fontsize=8)
plt.savefig(path + "RS image-first_band.png", dpi=300)
plt.clf()
# plt.imshow(RFHelper.training, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# plt.savefig(path + "Training_Image.png", dpi=300)
# plt.clf()
plt.imshow(RFHelper.prediction, cmap=plt.cm.Spectral)
plt.title('Prediction')
plt.savefig(path + "Prediction.png", dpi=300)
plt.clf()
# doc.line(20,800, 570, 800)
# doc.setLineWidth(.3)
# doc.setFont('Helvetica-Bold', 14)
# doc.drawString(30, 780, 'Section 1: General Information and Training')
# doc.drawString(30, 765, "Section 2: Validation")
# doc.line(20, 750, 570, 750)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 730, 'Section 1:')
doc.setFont('Helvetica', 14)
doc.drawString(30, 710,"Image extent: "+RFHelper.helper.imageExtent + "(Rows x Columns)")
doc.drawString(30, 690, "Number of Bands: "+ str(RFHelper.helper.BandNumber))
doc.drawString(30, 670, "Field name (shape file) of your classes: "+RFHelper.helper.FieldName)
doc.setFont('Helvetica', 14)
doc.drawString(30,650," Random Forrest Training")
doc.setFont('Helvetica', 14)
doc.drawString(30, 630, " Number of Tress: "+ str(RFHelper.helper.TreesNo))
doc.drawString(30, 610, " Number of samples: "+ str(RFHelper.helper.SampleNo))
doc.drawString(30, 590, " Split size for Test: "+str(RFHelper.helper.SplitSize))
doc.drawString(30, 570, " Training samples: "+str(RFHelper.helper.TrainingSample))
doc.drawString(30, 550, " Test sample: "+str(RFHelper.helper.TestSample))
doc.drawString(30, 530, "Co efficient of determination R^2 of the prediction : "+RFHelper.helper.Coeff)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 510, "left: ordered by band number| right: ordered by importance ")
data = ["Band", "Importance"]
data = [(k, v) for k, v in RFHelper.helper.BandImportance.items()]
# dummy = [('Band',1.33),('Band',5),('Band',4),('Band',2),('Band',6),('Band',8),('Band',43),('Band',3),('Band',113),('Band',233),('Band',13),('Band',133)]
# data.extend(dummy)
data2 = data[:]
data2.sort(key=lambda x: x[1], reverse=True)
data.insert(0, ("Band", "Importance"))
data2.insert(0, ("Band", "Importance"))
datalen = len(data)
print((datalen))
if(len(data)>21):
chunks = (self.chunks(data,20))
ordered_chunks = (self.chunks(data2, 20))
iterationNumer = 0
for unorder,ordered in zip(chunks,ordered_chunks):
if iterationNumer != 0:
unorder.insert(0, ("Band", "Importance"))
ordered.insert(0, ("Band", "Importance"))
unordered_table = Table(unorder)
ordered_table = Table(ordered)
unordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
ordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
if iterationNumer == 0:
unordered_table.wrapOn(doc, 60, 100)
unordered_table.drawOn(doc, 60, 100)
ordered_table.wrapOn(doc, 280, 100)
ordered_table.drawOn(doc,280, 100)
else:
unordered_table.wrapOn(doc, 60, 400)
unordered_table.drawOn(doc, 60, 400)
ordered_table.wrapOn(doc, 280, 400)
ordered_table.drawOn(doc, 280, 400)
columns = [""]
ordered_table = Table(columns)
unordered_table = Table(columns)
doc.showPage()
iterationNumer += 1
else:
table = Table(data)
table2 = Table(data2)
table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table.wrapOn(doc, 0,0)
table.drawOn(doc, 60, 100)
table2.wrapOn(doc, 60, 100)
table2.drawOn(doc, 280, 100)
doc.showPage()
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 790, 'Section 2:')
doc.setFont('Helvetica', 14)
doc.drawString(30, 770, "n of the data: " + str(RFHelper.helper.n_testdata))
doc.drawString(30, 750, "Mean of the Variable : " + str(RFHelper.helper.meanvariable))
doc.drawString(30, 730, "Standard Deviation of the Variable: " + str(round(RFHelper.helper.stdDev,2)))
doc.drawString(30, 710, "----------------------------------------")
doc.setFont('Helvetica', 14)
doc.drawString(30, 670, " Mean Absolute Error : " + str(round(RFHelper.helper.absError,2)))
doc.drawString(30, 650, " Mean Squared Error:" + str(round(RFHelper.helper.meanSqError,2)))
doc.drawString(30, 630, " RMSE:" + str(round(RFHelper.helper.RMSE,2)))
x = str(round(RFHelper.helper.MAPE,2))
doc.drawString(30, 600, " Mean absoulute percentage error(MAPE)/ Accuracy :" + x + " %")
doc.drawString(30, 560, "----------------------------------------")
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 540, "Co efficient of determination R^2 of the prediction : " + str(round(RFHelper.helper.coeffR,2)))
fig, ax = plt.subplots()
ax.scatter(RFHelper.helper.testlabels, RFHelper.helper.pred_test_ds)
ax.plot([RFHelper.helper.testlabels.min(), RFHelper.helper.testlabels.max()], [RFHelper.helper.testlabels.min(), RFHelper.helper.testlabels.max()], 'k--', lw=1)
ax.set_xlabel('Measured')
ax.set_ylabel('Predicted')
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
plt.savefig(path + "r2_Prediction.png", dpi=300)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 30, 110)
fig.clf()
plt.close(fig)
return doc
except ValueError as e:
logging.error("Exception occurred", exc_info=True)
print(e)
def make_plsr_sss_report(self, doc, img, dir_path, PLSR_SSS_Helper):
# self, doc, img, TrainingData, X, mse, msemin, component, y, y_c, y_cv, attribute, importance, prediction, dir_path, reportpath, prediction_map, modelsavepath, img_path, trn_path
try:
# reportparameters = PLSR_SSS_Helper()
# reportparameters = helpermodel
print(PLSR_SSS_Helper)
print(type(PLSR_SSS_Helper))
os.mkdir(dir_path + "/Graphs")
path = dir_path + "/Graphs/"
width, height = A4
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 705, "DIRECTORIES:")
doc.setFont('Helvetica', 10)
doc.drawString(30, 680, "Remote Sensing Image: " + str(PLSR_SSS_Helper.img_path))
doc.drawString(30, 660, "Shape file: " + str(PLSR_SSS_Helper.tran_path))
doc.drawString(30, 640, "Report Save Path: " + str(PLSR_SSS_Helper.reportpath))
doc.drawString(30, 620, "Regression image saved to: " + str(PLSR_SSS_Helper.prediction_map))
# if modelsavepath != '/':
doc.drawString(30, 600, "Model saved to: " + str(PLSR_SSS_Helper.modelsavepath))
# else:
# doc.drawString(30, 600, "Model saved to: Model not saved")
doc.line(20, 580, 570, 580)
mask = np.copy(img[:, :, 0])
mask[mask > 0.0] = 1.0 # all actual pixels have a value of 1.0
# plt.imshow(mask)
prediction_ = PLSR_SSS_Helper.prediction * mask
if img.shape[0] > img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(PLSR_SSS_Helper.train_data > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('first RS band and sample points', fontsize=8)
plt.subplot(122)
plt.imshow(prediction_, cmap=plt.cm.Spectral, vmin=PLSR_SSS_Helper.y.min(), vmax=PLSR_SSS_Helper.y.max())
plt.title('Prediction: ' + PLSR_SSS_Helper.attribute, fontsize=8)
plt.colorbar()
imgdata = BytesIO()
plt.savefig(path + "RS image-first_band.png", dpi=300)
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 160)
fig.clf()
plt.close(fig)
doc.showPage()
if img.shape[0] <= img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(PLSR_SSS_Helper.train_data > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('first RS band and sample points')
plt.subplot(122)
plt.imshow(prediction_, cmap=plt.cm.Spectral, vmin=PLSR_SSS_Helper.y.min(), vmax=PLSR_SSS_Helper.y.max())
plt.title('Prediction')
plt.colorbar()
imgdata = BytesIO()
plt.savefig(path + "RS image-first_band.png", dpi=300)
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 100, 160)
fig.clf()
plt.close(fig)
doc.showPage()
n_samples = (PLSR_SSS_Helper.train_data > 0).sum()
# doc.drawString(30, 720, 'We have {n} training samples'.format(n=n_samples))
# Subset the image dataset with the training image = X
# Mask the classes on the training dataset = y
# These will have n_samples rows
features = pd.DataFrame(PLSR_SSS_Helper.X)
band_names = []
for i in range(PLSR_SSS_Helper.X.shape[1]):
# for i in range(0,2500):
nband = "Band_" + str(i + 1)
band_names.append(nband)
features.columns = band_names
print(features.shape)
doc.line(20, 810, 570, 810)
doc.setLineWidth(.3)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 785, 'Section : General Information and Training')
doc.line(20, 770, 570, 770)
doc.setFont('Helvetica', 10)
doc.drawString(30, 700,
'The Image Extend: ' + str(img.shape[0]) + " x " + str(img.shape[1]) + " (Rows x Columns)")
doc.drawString(30, 680, 'The number of bands is: ' + str(features.shape[1]))
# doc.drawString(30, 680,'The shape of our features is: '+str(features.shape))
doc.drawString(30, 660, 'Selected Attribute: ' + str(PLSR_SSS_Helper.attribute))
doc.drawString(30, 640, 'The number of Sample is: ' + str(features.shape[0]))
doc.drawString(30, 620, '---------------------------------------------------------')
#
features['value'] = PLSR_SSS_Helper.y
features.head()
# Labels are the values we want to predict
labels = np.array(features['value'])
# Remove the labels from the features
# axis 1 refers to the columns
features = features.drop('value', axis=1)
# Saving feature names for later use
feature_list = list(features.columns)
# Convert to numpy array
features = np.array(features)
# doc.drawString(30, 620, 'Training Features Shape: ' + str(features.shape))
# doc.drawString(30, 600, 'Training Labels Shape: ' + str(labels.shape))
# return [doc, labels, features]
#
# doc.showPage()
suggested_comp = PLSR_SSS_Helper.msemin + 1
print("Suggested number of components: ", suggested_comp)
doc.drawString(30, 560, "Selected number of PLS components: " + str(suggested_comp))
fig = plt.figure(figsize=(5, 4))
with plt.style.context(('ggplot')):
plt.plot(PLSR_SSS_Helper.component, np.array(PLSR_SSS_Helper.mse), '-v', color='blue', mfc='blue')
plt.plot(PLSR_SSS_Helper.component[PLSR_SSS_Helper.msemin], np.array(PLSR_SSS_Helper.mse)[PLSR_SSS_Helper.msemin], 'P',
ms=10, mfc='red')
plt.xlabel('Number of PLS components')
plt.ylabel('MSE')
plt.title('PLSR MSE vs. Components')
plt.xlim(left=-1)
plt.savefig(path + "PLSR MSE vs. Components.png", dpi=300)
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 150)
fig.clf()
plt.close(fig)
doc.showPage()
score_c = r2_score(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_c)
score_cv = r2_score(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_cv)
# Calculate mean squared error for calibration and cross validation
mse_c = mean_squared_error(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_c)
mse_cv = mean_squared_error(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_cv)
# print("2 HERE!!!!!! mse_cv"+str(mse_cv))
print('R2 calib: %5.3f' % score_c)
doc.drawString(30, 730, 'R2 of the training: %5.3f' % score_c)
print('R2 LOOCV: %5.3f' % score_cv)
doc.drawString(30, 710, 'R2 LOOCV: %5.3f' % score_cv)
print('MSE calib: %5.3f' % mse_c)
doc.drawString(30, 690, 'MSE of the training: %5.3f' % mse_c)
print('MSE LOOCV: %5.3f' % mse_cv)
doc.drawString(30, 670, 'MSE LOOCV: %5.3f' % mse_cv)
imp = {}
for i in range(features.shape[1]):
print('Band {}: {}'.format(i + 1, round(PLSR_SSS_Helper.importance[i], 2)))
imp['Band{}'.format(i + 1)] = round(PLSR_SSS_Helper.importance[i], 2)
data = [(k, v) for k, v in imp.items()]
# dummy = [('Band',1.33),('Band',5),('Band',4),('Band',2),('Band',6),('Band',8),('Band',43),('Band',3),('Band',113),('Band',233),('Band',13),('Band',133)]
# data.extend(dummy)
data2 = data[:]
data2.sort(key=lambda x: x[1], reverse=True)
data.insert(0, ("Band", "Importance"))
data2.insert(0, ("Band", "Importance"))
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 510, "Band importance (left: ordered by band number | right: ordered by importance):")
doc.setFont('Helvetica', 10)
if (len(data) > 21):
chunks = (self.chunks(data, 20))
ordered_chunks = (self.chunks(data2, 20))
iterationNumer = 0
for unorder, ordered in zip(chunks, ordered_chunks):
if iterationNumer != 0:
unorder.insert(0, ("Band", "Importance"))
ordered.insert(0, ("Band", "Importance"))
unordered_table = Table(unorder)
ordered_table = Table(ordered)
unordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
ordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
if iterationNumer == 0:
unordered_table.wrapOn(doc, 60, 100)
unordered_table.drawOn(doc, 60, 100)
ordered_table.wrapOn(doc, 280, 100)
ordered_table.drawOn(doc, 280, 100)
else:
unordered_table.wrapOn(doc, 60, 400)
unordered_table.drawOn(doc, 60, 400)
ordered_table.wrapOn(doc, 280, 400)
ordered_table.drawOn(doc, 280, 400)
columns = [""]
ordered_table = Table(columns)
unordered_table = Table(columns)
doc.showPage()
iterationNumer += 1
else:
table = Table(data)
table2 = Table(data2)
table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table.wrapOn(doc, 0, 0)
table.drawOn(doc, 60, 100)
table2.wrapOn(doc, 60, 100)
table2.drawOn(doc, 280, 100)
doc.showPage()
doc.line(20, 810, 570, 810)
doc.setLineWidth(.3)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 785, 'Section : Validation')
doc.line(20, 770, 570, 770)
z = np.polyfit(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_c, 1)
with plt.style.context(('ggplot')):
fig, ax = plt.subplots(figsize=(5, 5))
ax.scatter(PLSR_SSS_Helper.y_c, PLSR_SSS_Helper.y, c='red', edgecolors='k')
# Plot the best fit line
ax.plot(np.polyval(z, PLSR_SSS_Helper.y), PLSR_SSS_Helper.y, c='blue', linewidth=1)
# Plot the ideal 1:1 line
ax.plot(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y, color='green', linewidth=1)
plt.title('$R^{2}$ (CV): ' + str(score_cv))
plt.xlabel('Predicted')
plt.ylabel('Measured')
plt.legend(['best fit line', 'ideal 1:1 line', 'samples'])
imgdata = BytesIO()
plt.savefig(path + "R2CV", dpi=300)
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 300)
fig.clf()
plt.close(fig)
# In[16]:
# Calculate the absolute errors
errors = abs(PLSR_SSS_Helper.y - PLSR_SSS_Helper.y_cv)
# Print out the mean absolute error (mae)
# Print out the mean absolute error (mae)
doc.setFont('Helvetica', 10)
doc.drawString(30, 270, '----------------------------')
print('-------------')
print('n of the test data: {}'.format(len(labels)))
doc.drawString(30, 250, 'n of the test data: ' + str((len(labels))))
print('Mean of the variable: {:.2f}'.format(np.mean(labels)))
doc.drawString(30, 230, 'Mean of the Samples: ' + str(round((np.mean(labels)), 2)))
print('Standard deviation of the variable: {:.2f}'.format(np.std(labels)))
doc.drawString(30, 210, 'Standard deviation of the Samples: ' + str(round(np.std(labels), 2)))
print('-------------')
doc.drawString(30, 190, '----------------------------')
print('Mean Absolute Error: {:.2f}'.format(np.mean(errors)))
doc.drawString(30, 170, 'MAE: ' + str(round(np.mean(errors), 2)))
print('Mean squared error: {:.2f}'.format(mse_cv))
doc.drawString(30, 150, 'MSE: ' + str(round(mse_cv, 2)))
print('RMSE: {:.2f}'.format(np.sqrt(mse_cv)))
doc.drawString(30, 130, 'RMSE: ' + str(round(np.sqrt(mse_cv), 2)))
RPD = np.std(labels) / np.sqrt(mse_cv)
print('RPD: {:.2f} | How often does RMSE of Prediction fit in the Standard Deviation of the samples'.format(
RPD))
doc.drawString(30, 110, 'RPD: ' + str(
round(RPD, 2)) + "| How often does RMSE of Prediction fit in the Standard Deviation of the samples")
mape = 100 * (errors / labels)
# Calculate and display accuracy
accuracy = 100 - np.mean(mape)
print('mean absolute percentage error (MAPE): {:.2f} %'.format(np.mean(mape)))
doc.drawString(30, 90, 'Mean Absolute Percentage Error (MAPE): ' + str(round(np.mean(mape), 2)) + " %")
print('accuracy (100 % - mape): {:.2f} %'.format(accuracy))
doc.drawString(30, 70, 'Accuracy (100 % - MAPE): ' + str(round(accuracy, 2)) + " %")
print('-------------')
doc.drawString(30, 50, '----------------------------')
# The coefficient of determination: 1 is perfect prediction
print('Coefficient of determination r²: {:.2f}'.format(r2_score(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_cv)))
doc.drawString(30, 30,
'Coefficient of determination r²: ' + str(round(r2_score(PLSR_SSS_Helper.y, PLSR_SSS_Helper.y_cv), 2)))
#
return doc
except ValueError as e:
logging.error("Exception occurred", exc_info=True)
print(e)
def make_plsr_lds_report(self,doc,dir_path,PLSR_LDS_Helper):
os.mkdir(dir_path+"/Graphs")
path = dir_path +"/Graphs/"
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 705, "DIRECTORIES:")
doc.setFont('Helvetica', 10)
doc.drawString(30, 680, "Remote Sensing Image: " + str(PLSR_LDS_Helper.img_path))
doc.drawString(30, 660, "Shape file: " + str(PLSR_LDS_Helper.tran_path))
doc.drawString(30, 640, "Report Save Path: " + str(PLSR_LDS_Helper.reportpath))
doc.drawString(30, 620, "Regression image saved to: " + str(PLSR_LDS_Helper.prediction_map))
# if modelsavepath != '/':
doc.drawString(30, 600, "Model saved to: " + str(PLSR_LDS_Helper.modelsavepath))
doc.line(20, 580, 570, 580)
mask = np.copy(PLSR_LDS_Helper.img[:, :, 0])
mask[mask > 0.0] = 1.0 # all actual pixels have a value of 1.0
prediction_ = PLSR_LDS_Helper.prediction * mask
if PLSR_LDS_Helper.img.shape[0] > PLSR_LDS_Helper.img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
print(PLSR_LDS_Helper.img.shape)
plt.imshow(PLSR_LDS_Helper.img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(PLSR_LDS_Helper.train_data > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
# plt.subplot(122)
# plt.imshow(PLSR_LDS_Helper.train_data, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 160)
# else:
# renderPDF.draw(drawing, doc, 50, 250)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(PLSR_LDS_Helper.prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 400, 160)
fig.clf()
plt.close(fig)
doc.showPage()
if PLSR_LDS_Helper.img.shape[0] <= PLSR_LDS_Helper.img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
print(PLSR_LDS_Helper.img.shape)
plt.imshow(PLSR_LDS_Helper.img[:, :, 0], cmap=plt.cm.Greys_r)
roi_positions = np.where(PLSR_LDS_Helper.train_data > 0)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
# plt.subplot(122)
# plt.imshow(PLSR_LDS_Helper.train_data, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 160)
# else:
# renderPDF.draw(drawing, doc, 50, 250)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(PLSR_LDS_Helper.prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 100, 160)
fig.clf()
plt.close(fig)
doc.showPage()
roi_positions = np.where(PLSR_LDS_Helper.train_data > 0)
plt.imshow(PLSR_LDS_Helper.img[:, :, 0], cmap=plt.cm.Greys_r)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
plt.savefig(path + "RS image-first_band.png", dpi=300)
plt.clf()
# plt.imshow(PLSR_LDS_Helper.train_data, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# plt.savefig(path + "Training_Image.png", dpi=300)
# plt.clf()
plt.imshow(PLSR_LDS_Helper.prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
plt.savefig(path + "Prediction.png", dpi=300)
plt.clf()
n_samples = (PLSR_LDS_Helper.train_data > 0).sum()
print(
'We have {n} training samples'.format(n=n_samples)) # Subset the image dataset with the training image = X
print('The shape of our features is:', PLSR_LDS_Helper.features.shape)
print('The number of Spectra is:', PLSR_LDS_Helper.features.shape[0])
print('The number of bands is:', PLSR_LDS_Helper.features.shape[1])
doc.line(20, 810, 570, 810)
doc.setLineWidth(.3)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 785, 'Section : General Information and Training')
doc.line(20, 770, 570, 770)
doc.setFont('Helvetica', 10)
doc.drawString(30, 700,
'The Image Extend: ' + str(PLSR_LDS_Helper.img.shape[0]) + " x " + str(PLSR_LDS_Helper.img.shape[1]) + " (Rows x Columns)")
doc.drawString(30, 680, 'The number of bands is: ' + str(PLSR_LDS_Helper.features.shape[1]))
# doc.drawString(30, 680,'The shape of our features is: '+str(features.shape))
doc.drawString(30, 660, 'Selected Attribute: ' + str(PLSR_LDS_Helper.attribute))
doc.drawString(30, 640, 'The number of Sample is: ' + str(PLSR_LDS_Helper.features.shape[0]))
doc.drawString(30, 620, '---------------------------------------------------------')
# from sklearn import preprocessing
#
# min_max_scaler = preprocessing.MinMaxScaler()
#
# xscaled = min_max_scaler.fit_transform(features)
# features_ = pd.DataFrame(xscaled)
#
# features_.transpose().plot(figsize=(20, 7))
# plt.legend(bbox_to_anchor=(0.1, -0.1), loc='upper left', ncol=7)
# plt.title('Reference Spectra')
# plt.plot()
#
#
print('Training Features Shape:', PLSR_LDS_Helper.train_features.shape)
print('Training Labels Shape:', PLSR_LDS_Helper.train_labels.shape)
print('Testing Features Shape:', PLSR_LDS_Helper.test_features.shape)
print('Testing Labels Shape:', PLSR_LDS_Helper.test_labels.shape)
#
msemin = np.argmin(PLSR_LDS_Helper.mse)
suggested_comp = msemin + 1
print("Suggested number of components: ", suggested_comp)
fig = plt.figure(figsize=(5, 4))
with plt.style.context(('ggplot')):
plt.plot(PLSR_LDS_Helper.component, np.array(PLSR_LDS_Helper.mse), '-v', color='blue', mfc='blue')
plt.plot(PLSR_LDS_Helper.component[msemin], np.array(PLSR_LDS_Helper.mse)[msemin], 'P', ms=10, mfc='red')
plt.xlabel('Number of PLS components')
plt.ylabel('MSE')
plt.title('PLSR MSE vs. Components')
plt.xlim(left=-1)
plt.savefig(path + "PLSR MSE vs. Components.png", dpi=300)
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 150)
fig.clf()
plt.close(fig)
doc.showPage()
# print(sorted_imp)
imp = {}
for i in range(PLSR_LDS_Helper.features.shape[1]):
print('Band {}: {}'.format(i + 1, round(PLSR_LDS_Helper.importance[i], 2)))
imp['Band{}'.format(i + 1)] = round(PLSR_LDS_Helper.importance[i], 2)
data = [(k, v) for k, v in imp.items()]
# dummy = [('Band',1.33),('Band',5),('Band',4),('Band',2),('Band',6),('Band',8),('Band',43),('Band',3),('Band',113),('Band',233),('Band',13),('Band',133)]
# data.extend(dummy)
data2 = data[:]
data2.sort(key=lambda x: x[1], reverse=True)
data.insert(0, ("Band", "Importance"))
data2.insert(0, ("Band", "Importance"))
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 710, "Band importance (left: ordered by band number | right: ordered by importance):")
doc.setFont('Helvetica', 10)
if (len(data) > 21):
chunks = (self.chunks(data, 20))
ordered_chunks = (self.chunks(data2, 20))
iterationNumer = 0
for unorder, ordered in zip(chunks, ordered_chunks):
if iterationNumer != 0:
unorder.insert(0, ("Band", "Importance"))
ordered.insert(0, ("Band", "Importance"))
unordered_table = Table(unorder)
ordered_table = Table(ordered)
unordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
ordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
if iterationNumer == 0:
unordered_table.wrapOn(doc, 60, 100)
unordered_table.drawOn(doc, 60, 100)
ordered_table.wrapOn(doc, 280, 100)
ordered_table.drawOn(doc, 280, 100)
else:
unordered_table.wrapOn(doc, 60, 400)
unordered_table.drawOn(doc, 60, 400)
ordered_table.wrapOn(doc, 280, 400)
ordered_table.drawOn(doc, 280, 400)
columns = [""]
ordered_table = Table(columns)
unordered_table = Table(columns)
doc.showPage()
iterationNumer += 1
else:
table = Table(data)
table2 = Table(data2)
table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table.wrapOn(doc, 0, 0)
table.drawOn(doc, 60, 100)
table2.wrapOn(doc, 60, 100)
table2.drawOn(doc, 280, 100)
doc.showPage()
#
errors = abs(PLSR_LDS_Helper.predictions_test_ds - PLSR_LDS_Helper.test_labels)
# Print out the mean absolute error (mae)
# Print out the mean absolute error (mae)
print('-------------')
print('n of the test data: {}'.format(len(PLSR_LDS_Helper.test_labels)))
print('Mean of the variable: {:.2f}'.format(np.mean(PLSR_LDS_Helper.labels)))
print('Standard deviation of the variable: {:.2f}'.format(np.std(PLSR_LDS_Helper.labels)))
print('-------------')
print('Mean Absolute Error: {:.2f}'.format(np.mean(errors)))
mse = mean_squared_error(PLSR_LDS_Helper.test_labels, PLSR_LDS_Helper.predictions_test_ds)
print('Mean squared error: '+ str(round(mse,2)))
print('RMSE: '+str(round(np.sqrt(mse),2)))
#
mape = 100 * (errors / PLSR_LDS_Helper.test_labels)
# Calculate and display accuracy
accuracy = 100 - np.mean(mape)
print('mean absolute percentage error (MAPE) / Accuracy: {:.2f}'.format(accuracy), '%.')
print('-------------')
# The coefficient of determination: 1 is perfect prediction
print('Coefficient of determination r²: {:.2f}'.format(r2_score(PLSR_LDS_Helper.test_labels, PLSR_LDS_Helper.predictions_test_ds)))
# #
doc.drawString(30, 785, 'n of the test data: {}'.format(len(PLSR_LDS_Helper.test_labels)))
doc.drawString(30, 765,'Mean of the variable: {:.2f}'.format(np.mean(PLSR_LDS_Helper.labels)))
doc.drawString(30, 745,'Standard deviation of the variable: {:.2f}'.format(np.std(PLSR_LDS_Helper.labels)))
doc.drawString(30, 735,'------------------------------------------------------')
doc.drawString(30, 715,'Mean Absolute Error: {:.2f}'.format(np.mean(errors)))
mse = mean_squared_error(PLSR_LDS_Helper.test_labels, PLSR_LDS_Helper.predictions_test_ds)
doc.drawString(30, 685,'Mean squared error: {:.2f}'.format(mse))
doc.drawString(30, 670,'RMSE: {:.2f}'.format(np.sqrt(mse)))
mape = 100 * (errors / PLSR_LDS_Helper.test_labels)
# Calculate and display accuracy
accuracy = 100 - np.mean(mape)
doc.drawString(30, 655,"mean absolute percentage error (MAPE) / Accuracy: "+ str(round(accuracy,2))+" %")
doc.drawString(30, 640,'----------------------------------------------------')
fig, ax = plt.subplots(figsize=(5,5))
ax.scatter(PLSR_LDS_Helper.test_labels, PLSR_LDS_Helper.predictions_test_ds)
ax.plot([PLSR_LDS_Helper.test_labels.min(), PLSR_LDS_Helper.test_labels.max()], [PLSR_LDS_Helper.test_labels.min(), PLSR_LDS_Helper.test_labels.max()], 'k--', lw=1)
ax.set_xlabel('Measured')
ax.set_ylabel('Predicted')
imgdata = BytesIO()
plt.savefig(path + "R2CV", dpi=300)
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 240)
fig.clf()
plt.close(fig)
# mask = np.copy(img[:, :, 0])
# mask[mask > 0.0] = 1.0 # all actual pixels have a value of 1.0
# plot mask
# plt.imshow(mask)
# mask classification an plot
# prediction_ = prediction * mask
#
# plt.subplot(121)
# plt.imshow(prediction, cmap=plt.cm.Spectral, vmax=prediction.mean() + prediction.std() * 2,
# vmin=prediction.mean() - prediction.std() * 2)
# plt.title('prediction unmasked')
#
# plt.subplot(122)
# plt.imshow(prediction_, cmap=plt.cm.Spectral, vmax=prediction_.mean() + prediction_.std() * 2,
# vmin=prediction_.mean() - prediction_.std() * 2)
# plt.title('prediction masked')
#
# plt.show()
#
#
# plt.subplot(121)
# plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
# plt.title('RS image - first band')
#
# plt.subplot(122)
# plt.imshow(prediction, cmap=plt.cm.Spectral, vmax=prediction_.mean() + prediction_.std() * 2,
# vmin=prediction_.mean() - prediction_.std() * 2)
# plt.colorbar()
#
# plt.title('Prediction')
#
# plt.show()
#
return doc
def make_rfr_sss_report(self,doc,reportpath,dir_path,train_data,prediction_map,modelsavepath,img_path,TrainingData,img,attributes,prediction, y_c, y_cv, RFR):
try:
os.mkdir(dir_path + "/Graphs")
path = dir_path + "/Graphs/"
width, height = A4
# print("here........."+reportpath)
print(prediction_map)
print(modelsavepath)
print(img_path)
print(train_data)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 700,"DIRECTORIES:")
doc.setFont('Helvetica', 7)
doc.drawString(30, 680, "Remote Sensing Image: " + img_path)
doc.drawString(30, 660, "Shape file: " + train_data)
doc.drawString(30, 640, "Report Save Path: "+ reportpath)
doc.drawString(30, 620, "Regression image saved to: " + prediction_map)
if modelsavepath !='/':
doc.drawString(30, 600, "Model saved to: "+modelsavepath)
else:
doc.drawString(30, 600, "Model saved to: Model not saved")
doc.line(20, 580, 570, 580)
n_samples = (TrainingData > 0).sum()
print('We have {n} training samples'.format(
n=n_samples)) # Subset the image dataset with the training image = X
roi_positions = np.where(TrainingData > 0)
if img.shape[0] > img.shape[1]:
fig = plt.figure(figsize=(5, 4))
plt.subplot(121)
print(img.shape)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
# plt.subplot(122)
# plt.imshow(TrainingData, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# #plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 160)
# else:
# renderPDF.draw(drawing, doc, 50, 250)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 400, 160)
fig.clf()
plt.close(fig)
doc.showPage()
if img.shape[0]<= img.shape[1]:
fig = plt.figure(figsize=(6, 4))
plt.subplot(121)
print(img.shape)
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
# plt.subplot(122)
# plt.imshow(TrainingData, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
# plt.title('Training Image')
# #plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 50, 360)
# else:
# renderPDF.draw(drawing, doc, 50, 250)
fig.clf()
plt.close(fig)
fig = plt.figure(figsize=(5, 4))
plt.imshow(prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
# plt.show()
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 70, 60)
fig.clf()
plt.close(fig)
doc.showPage()
plt.imshow(img[:, :, 0], cmap=plt.cm.Greys_r)
plt.scatter(roi_positions[1], roi_positions[0], marker='x', c='r')
plt.title('RS image - first band')
plt.savefig(path + "RS image-first_band.png", dpi=300)
plt.clf()
plt.imshow(TrainingData, cmap=plt.cm.Spectral) # data = roi && cmap = plt.cm.Spectral
plt.title('Training Image')
plt.savefig(path + "Training_Image.png", dpi=300)
plt.clf()
plt.imshow(prediction, cmap=plt.cm.Spectral)
plt.colorbar()
plt.title('Prediction')
plt.savefig(path + "Prediction.png", dpi=300)
plt.clf()
settings_sns = {'axes.facecolor': 'white',
'axes.edgecolor': '0',
'axes.grid': True,
'axes.axisbelow': True,
'axes.labelcolor': '.15',
'figure.facecolor': 'white',
'grid.color': '.8',
'grid.linestyle': '--',
'text.color': '0',
'xtick.color': '0',
'ytick.color': '0',
'xtick.direction': 'in',
'ytick.direction': 'in',
'lines.solid_capstyle': 'round',
'patch.edgecolor': 'w',
'patch.force_edgecolor': True,
'image.cmap': 'Greys',
'font.family': ['serif'],
'font.sans-serif': ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans',
'sans-serif'],
'xtick.bottom': True,
'xtick.top': True,
'ytick.left': True,
'ytick.right': True,
'axes.spines.left': True,
'axes.spines.bottom': True,
'axes.spines.right': True,
'axes.spines.top': True}
X = img[TrainingData > 0, :]
y = TrainingData[TrainingData > 0]
features = pd.DataFrame(X)
band_names = []
for i in range(X.shape[1]):
# for i in range(0,2500):
nband = "Band_" + str(i + 1)
band_names.append(nband)
# print("*******************")
# print(band_names)
# print("*******************")
features.columns = band_names
print('The shape of our features is:', features.shape)
print('The number of Spectra is:', features.shape[0])
print('The number of bands is:', features.shape[1])
features['value'] = y
# min_max_scaler = preprocessing.MinMaxScaler()
#
# xscaled = min_max_scaler.fit_transform(features)
# features_ = pd.DataFrame(xscaled)
#
# features_.transpose().plot(figsize=(20, 7))
# plt.legend(bbox_to_anchor=(0.1, -0.1), loc='upper left', ncol=7)
# plt.title('Reference Spectra')
# plt.plot()
#
# # # In[10]:
# Labels are the values we want to predict
labels = np.array(features['value'])
# Remove the labels from the features
# axis 1 refers to the columns
features = features.drop('value', axis=1)
# Saving feature names for later use
feature_list = list(features.columns)
# Convert to numpy array
features = np.array(features)
print('Training Features Shape: ', features.shape)
print('Training Labels Shape: ', labels.shape)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 730, 'Section 1:')
doc.setFont('Helvetica', 14)
doc.drawString(30, 710, "Image extent: " + str(img.shape[0]) +" x "+ str(img.shape[1]) + " (Rows x Columns)")
doc.drawString(30, 690, "Number of Bands: " + str(features.shape[1]))
doc.drawString(30, 670, "Field name (shape file) of your classes: " + attributes)
doc.setFont('Helvetica', 14)
doc.drawString(30, 650, " Random Forrest Training")
doc.setFont('Helvetica', 14)
doc.drawString(30, 630, " Number of Tress: " )
doc.drawString(30, 610, " Number of samples: " + str(n_samples))
#doc.drawString(30, 590, " Split size for Test: " + str(RFHelper.helper.SplitSize))
#doc.drawString(30, 570, " Training samples: " + str(labels.shape[0]))
#doc.drawString(30, 550, " Test sample: " + str(RFHelper.helper.TestSample))
#doc.drawString(30, 530, "Co efficient of determination R^2 of the prediction : " + RFHelper.helper.Coeff)
doc.setFont('Helvetica-Bold', 14)
doc.drawString(30, 510, "left: ordered by band number| right: ordered by importance ")
imp = {}
for i in range(len(RFR.feature_importances_)):
importance = round(RFR.feature_importances_[i] * 100, 2)
print('Band {}: {}'.format(i + 1, importance))
imp['Band{}'.format(i + 1)] = importance
data = [(k, v) for k, v in imp.items()]
data2 = data[:]
data2.sort(key=lambda x: x[1], reverse=True)
data.insert(0, ("Band", "Importance"))
data2.insert(0, ("Band", "Importance"))
doc.setFont('Helvetica', 10)
if (len(data) > 21):
chunks = (self.chunks(data, 20))
ordered_chunks = (self.chunks(data2, 20))
iterationNumer = 0
for unorder, ordered in zip(chunks, ordered_chunks):
if iterationNumer != 0:
unorder.insert(0, ("Band", "Importance"))
ordered.insert(0, ("Band", "Importance"))
unordered_table = Table(unorder)
ordered_table = Table(ordered)
unordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
ordered_table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
if iterationNumer == 0:
unordered_table.wrapOn(doc, 60, 100)
unordered_table.drawOn(doc, 60, 100)
ordered_table.wrapOn(doc, 280, 100)
ordered_table.drawOn(doc, 280, 100)
else:
unordered_table.wrapOn(doc, 60, 400)
unordered_table.drawOn(doc, 60, 400)
ordered_table.wrapOn(doc, 280, 400)
ordered_table.drawOn(doc, 280, 400)
columns = [""]
ordered_table = Table(columns)
unordered_table = Table(columns)
doc.showPage()
iterationNumer += 1
else:
table = Table(data)
table2 = Table(data2)
table.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table2.setStyle(TableStyle([("BOX", (0, 0), (-1, -1), 0.25, colors.black),
('INNERGRID', (0, 0), (-1, -1), 0.25, colors.black)]))
table.wrapOn(doc, 0, 0)
table.drawOn(doc, 60, 100)
table2.wrapOn(doc, 60, 100)
table2.drawOn(doc, 280, 100)
doc.showPage()
score_c = r2_score(y, y_c)
score_cv = r2_score(y, y_cv)
mse_c = mean_squared_error(y, y_c)
mse_cv = mean_squared_error(y, y_cv)
errors = abs(y_cv - labels)
# Print out the mean absolute error (mae)
# Print out the mean absolute error (mae)
print('-------------')
print('n of the test data: {}'.format(len(labels)))
print('Mean of the variable: {:.2f}'.format(np.mean(labels)))
print('Standard deviation of the variable: {:.2f}'.format(np.std(labels)))
print('-------------')
print('Mean Absolute Error: {:.2f}'.format(np.mean(errors)))
mse = mean_squared_error(labels, y_cv)
print('Mean squared error: {:.2f}'.format(mse))
print('RMSE: {:.2f}'.format(np.sqrt(mse)))
print(
'RPD: {:.2f} | How often does RMSE of Prediction fit in the Standard Deviation of the samples'.format(
np.std(labels) / np.sqrt(mse)))
doc.drawString(30, 770, "n of the data: " + str(len(labels)))
doc.drawString(30, 750, "Mean of the Variable : " + str(np.mean(labels)))
doc.drawString(30, 730, "Standard Deviation of the Variable: " + str(round(np.std(labels), 2)))
doc.drawString(30, 710, "----------------------------------------")
doc.setFont('Helvetica', 14)
doc.drawString(30, 670, " Mean Absolute Error : " + str(round(np.mean(errors), 2)))
doc.drawString(30, 650, " Mean Squared Error:" + str(round(mse, 2)))
doc.drawString(30, 630, " RMSE:" + str(round(np.sqrt(mse), 2)))
doc.drawString(30, 600, 'RPD:'+ str(round(np.std(labels) / np.sqrt(mse),2)))
doc.setFont('Helvetica', 10)
doc.drawString(30, 580,'How often does RMSE of Prediction fit in the Standard Deviation of the samples')
doc.drawString(30, 560, "----------------------------------------")
mape = 100 * (errors / labels)
# Calculate and display accuracy
accuracy = 100 - np.mean(mape)
print('mean absolute percentage error (MAPE) / Accuracy: {:.2f}'.format(accuracy), '%.')
print('-------------')
doc.setFont('Helvetica', 14)
doc.drawString(30, 530,'mean absolute percentage error (MAPE) / Accuracy:'+ str(round(accuracy,2))+ ' %.')
# The coefficient of determination: 1 is perfect prediction
print('Coefficient of determination r²: {:.2f}'.format(r2_score(labels, y_cv)))
doc.drawString(30, 510,'Coefficient of determination r²: '+ str(round(r2_score(labels, y_cv),2)))
'''
To put our predictions in perspective, we can calculate an accuracy using
the mean average percentage error subtracted from 100 %.
'''
# Calculate mean absolute percentage error (MAPE)
print('R2 calib: %5.3f' % score_c)
print('R2 LOOCV: %5.3f' % score_cv)
print('MSE calib: %5.3f' % mse_c)
print('MSE LOOCV: %5.3f' % mse_cv)
# In[12]:
#
# Plot regression and figures of merit
rangey = max(y) - min(y)
rangex = max(y_c) - min(y_c)
# Fit a line to the CV vs response
z = np.polyfit(y, y_c, 1)
with plt.style.context(('ggplot')):
sns.set(rc=settings_sns, font_scale=1.0)
fig, ax = plt.subplots(figsize=(7, 5))
ax.scatter(y_c, y, c='red', edgecolors='k')
# Plot the best fit line
ax.plot(np.polyval(z, y), y, c='blue', linewidth=1)
# Plot the ideal 1:1 line
ax.plot(y, y, color='green', linewidth=1)
plt.title(attributes)
plt.xlabel('predicted')
plt.ylabel('observed')
plt.legend(['regression \nr$^{2}$ (CV): ' + str(round(score_cv, 2)), '1:1 line', 'samples'])
imgdata = BytesIO()
fig.savefig(imgdata, format='svg', bbox_inches='tight', pad_inches=0)
plt.savefig(path + "r2_Prediction.png", dpi=300)
imgdata.seek(0) # rewind the data
drawing = svg2rlg(imgdata)
renderPDF.draw(drawing, doc, 30, 70)
fig.clf()
plt.close(fig)
#
return doc
except ValueError as e:
print(e)
def chunks(self,lst, n):
return [lst[i:i + n] for i in range(0, len(lst), n)]
| 43.741917 | 187 | 0.512425 | 8,463 | 74,405 | 4.415574 | 0.071724 | 0.051834 | 0.059006 | 0.00471 | 0.824748 | 0.78996 | 0.760711 | 0.738634 | 0.717921 | 0.693998 | 0 | 0.057626 | 0.340905 | 74,405 | 1,700 | 188 | 43.767647 | 0.704384 | 0.126107 | 0 | 0.669964 | 0 | 0 | 0.135907 | 0.00902 | 0 | 0 | 0 | 0 | 0 | 1 | 0.007194 | false | 0 | 0.063849 | 0.000899 | 0.079137 | 0.080036 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
759268858439efc82b914933e670f5255e4ba7ec | 63 | py | Python | utils/__init__.py | Tiamat-Tech/ZAQ-code | e7e9f55791e36c6784d58c356d3ced76a7583369 | [
"MIT"
] | 55 | 2021-03-30T01:30:46.000Z | 2022-03-30T03:05:25.000Z | utils/__init__.py | Tiamat-Tech/ZAQ-code | e7e9f55791e36c6784d58c356d3ced76a7583369 | [
"MIT"
] | 8 | 2021-04-23T07:59:20.000Z | 2021-06-04T14:28:24.000Z | utils/__init__.py | Tiamat-Tech/ZAQ-code | e7e9f55791e36c6784d58c356d3ced76a7583369 | [
"MIT"
] | 13 | 2021-04-08T03:15:47.000Z | 2022-03-18T08:39:12.000Z | from .loss import *
from . import misc
from . import visualizer | 21 | 24 | 0.761905 | 9 | 63 | 5.333333 | 0.555556 | 0.416667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.174603 | 63 | 3 | 24 | 21 | 0.923077 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
7598cb4d560c120c6dc251a42bd76ee8f67a914e | 149 | py | Python | medal/models/__init__.py | JaniceLC/O-MedAL | c0e1cc3db0005a4b88edbeb2c077e5e46621945d | [
"MIT"
] | 13 | 2019-08-29T06:04:15.000Z | 2021-02-23T03:49:38.000Z | medal/models/__init__.py | JaniceLC/O-MedAL | c0e1cc3db0005a4b88edbeb2c077e5e46621945d | [
"MIT"
] | 1 | 2019-11-05T08:02:23.000Z | 2019-11-05T09:03:30.000Z | medal/models/__init__.py | JaniceLC/O-MedAL | c0e1cc3db0005a4b88edbeb2c077e5e46621945d | [
"MIT"
] | 11 | 2019-10-13T23:12:41.000Z | 2021-05-06T14:22:21.000Z | from .inception import InceptionV3BinaryClassifier
from .squeezenet import SqueezeNetBinaryClassifier
from .resnet18 import Resnet18BinaryClassifier
| 37.25 | 50 | 0.899329 | 12 | 149 | 11.166667 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.036496 | 0.080537 | 149 | 3 | 51 | 49.666667 | 0.941606 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
75aabd1c603ddb338a814daa8437226eab511826 | 333 | py | Python | features/extraction/lib/__init__.py | bayesimpact/readmission-risk | 5b0f6c93826601e2dbb9c8c276e92801772e17c4 | [
"Apache-2.0"
] | 19 | 2016-10-06T18:10:36.000Z | 2018-04-04T02:30:09.000Z | features/extraction/lib/__init__.py | BeaconLabs/readmission-risk | 5b0f6c93826601e2dbb9c8c276e92801772e17c4 | [
"Apache-2.0"
] | 2 | 2017-10-26T19:22:58.000Z | 2017-11-16T07:44:58.000Z | features/extraction/lib/__init__.py | bayesimpact/readmission-risk | 5b0f6c93826601e2dbb9c8c276e92801772e17c4 | [
"Apache-2.0"
] | 9 | 2016-11-15T14:13:20.000Z | 2021-12-19T20:27:58.000Z | """
Helper methods and classes, organized by category.
Some are specific to this project, others are more general (e.g. databuilder.py
is used with modifications throughout different Bayes projects).
TODO: Separate this out into general utility methods/classes and sutter-specific stuff.
"""
from __future__ import absolute_import
| 33.3 | 87 | 0.804805 | 47 | 333 | 5.595745 | 0.829787 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.138138 | 333 | 9 | 88 | 37 | 0.916376 | 0.855856 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
75c293f148372f5eff803450c78fb78000cc268d | 35 | py | Python | spinesTS/pipeline/__init__.py | BirchKwok/spinesTS | b88ec333f41f58979e0570177d1fdc364d976056 | [
"Apache-2.0"
] | 2 | 2021-08-15T09:29:37.000Z | 2022-03-10T13:56:13.000Z | spinesTS/pipeline/__init__.py | BirchKwok/spinesTS | b88ec333f41f58979e0570177d1fdc364d976056 | [
"Apache-2.0"
] | null | null | null | spinesTS/pipeline/__init__.py | BirchKwok/spinesTS | b88ec333f41f58979e0570177d1fdc364d976056 | [
"Apache-2.0"
] | null | null | null | from ._pipeline import Pipeline
| 11.666667 | 32 | 0.771429 | 4 | 35 | 6.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 35 | 2 | 33 | 17.5 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
75c7fa6ddf60415d6fc6e4d53494a03dda06a234 | 118 | py | Python | shoppon/db/sqlalchemy/versions/001_init.py | shoppon/Python-learning | 50b68785b6b3b78a7deba3f452fa9c0fad218e9b | [
"MIT"
] | null | null | null | shoppon/db/sqlalchemy/versions/001_init.py | shoppon/Python-learning | 50b68785b6b3b78a7deba3f452fa9c0fad218e9b | [
"MIT"
] | null | null | null | shoppon/db/sqlalchemy/versions/001_init.py | shoppon/Python-learning | 50b68785b6b3b78a7deba3f452fa9c0fad218e9b | [
"MIT"
] | null | null | null | from sqlalchemy import Integer
from sqlalchemy import Table
def upgrade(migrate_engine):
Table('fake', Integer()) | 23.6 | 30 | 0.779661 | 15 | 118 | 6.066667 | 0.666667 | 0.307692 | 0.43956 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135593 | 118 | 5 | 31 | 23.6 | 0.892157 | 0 | 0 | 0 | 0 | 0 | 0.033613 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.5 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
75f51b46f750aaeca5a585973aa3bb8c2ca8f19f | 450 | py | Python | regresspy/loss.py | roman1117459/regress_py_package | 393f804a653858fc66f620cd50ee022b43fb5d90 | [
"MIT"
] | 1 | 2021-08-15T20:27:20.000Z | 2021-08-15T20:27:20.000Z | regresspy/loss.py | roman1117459/regress_py_package | 393f804a653858fc66f620cd50ee022b43fb5d90 | [
"MIT"
] | null | null | null | regresspy/loss.py | roman1117459/regress_py_package | 393f804a653858fc66f620cd50ee022b43fb5d90 | [
"MIT"
] | 2 | 2021-08-18T14:44:39.000Z | 2021-08-22T04:24:44.000Z | import numpy as np
from numpy import ndarray
def mae(pred: ndarray, label: ndarray) -> ndarray:
return np.mean(np.abs(label - pred))
def sse(pred: ndarray, label: ndarray) -> ndarray:
return np.sum(np.power((label - pred), 2))
def mse(pred: ndarray, label: ndarray) -> ndarray:
return np.mean(np.power((label - pred), 2))
def rmse(pred: ndarray, label: ndarray) -> ndarray:
return np.sqrt(np.mean(np.power((label - pred), 2))) | 25 | 56 | 0.666667 | 69 | 450 | 4.347826 | 0.289855 | 0.146667 | 0.213333 | 0.306667 | 0.75 | 0.75 | 0.673333 | 0.293333 | 0.293333 | 0 | 0 | 0.008065 | 0.173333 | 450 | 18 | 56 | 25 | 0.798387 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0.2 | 0.4 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
75f8010aa51a5b01978256adeef78df9b5f3ef2c | 42 | py | Python | c42_csr2postman/models/__init__.py | 42c-presales/42c-report-scan-to-postman | 1d9a4965d54d2fd28944367894896f2ace9c74e9 | [
"Apache-2.0"
] | 1 | 2021-12-30T21:20:35.000Z | 2021-12-30T21:20:35.000Z | c42_csr2postman/models/__init__.py | 42c-presales/42c-report-scan-to-postman | 1d9a4965d54d2fd28944367894896f2ace9c74e9 | [
"Apache-2.0"
] | null | null | null | c42_csr2postman/models/__init__.py | 42c-presales/42c-report-scan-to-postman | 1d9a4965d54d2fd28944367894896f2ace9c74e9 | [
"Apache-2.0"
] | null | null | null | from .csr import *
from .postman import *
| 14 | 22 | 0.714286 | 6 | 42 | 5 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.190476 | 42 | 2 | 23 | 21 | 0.882353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
75fd08c544f319e7a6fc21965862c37e24234f66 | 41 | py | Python | __init__.py | Bejjox/BejjoLib | ba0e595d40b49a025ef37ca3122c7b25d1a7ecca | [
"MIT"
] | 1 | 2020-07-14T17:09:19.000Z | 2020-07-14T17:09:19.000Z | __init__.py | Bejjox/BejjoLib | ba0e595d40b49a025ef37ca3122c7b25d1a7ecca | [
"MIT"
] | 1 | 2020-11-01T15:24:36.000Z | 2020-11-01T15:25:09.000Z | __init__.py | Bejjox/BejjoLib | ba0e595d40b49a025ef37ca3122c7b25d1a7ecca | [
"MIT"
] | 1 | 2020-07-14T17:09:31.000Z | 2020-07-14T17:09:31.000Z | from .randm import *
from .num2w import * | 20.5 | 20 | 0.731707 | 6 | 41 | 5 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029412 | 0.170732 | 41 | 2 | 21 | 20.5 | 0.852941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
f9b45cd6d53ca724fb43e8156ddb45327693663b | 12,447 | py | Python | vimfiles/bundle/vim-python/submodules/pylint/tests/checkers/unittest_deprecated.py | ciskoinch8/vimrc | 5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8 | [
"MIT"
] | 463 | 2015-01-15T08:17:42.000Z | 2022-03-28T15:10:20.000Z | vimfiles/bundle/vim-python/submodules/pylint/tests/checkers/unittest_deprecated.py | ciskoinch8/vimrc | 5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8 | [
"MIT"
] | 52 | 2015-01-06T02:43:59.000Z | 2022-03-14T11:15:21.000Z | vimfiles/bundle/vim-python/submodules/pylint/tests/checkers/unittest_deprecated.py | ciskoinch8/vimrc | 5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8 | [
"MIT"
] | 249 | 2015-01-07T22:49:49.000Z | 2022-03-18T02:32:06.000Z | import astroid
from pylint.checkers import BaseChecker, DeprecatedMixin
from pylint.interfaces import UNDEFINED, IAstroidChecker
from pylint.testutils import CheckerTestCase, Message
class _DeprecatedChecker(DeprecatedMixin, BaseChecker):
__implements__ = (IAstroidChecker,)
name = "deprecated"
def deprecated_methods(self):
return {"deprecated_func", ".Deprecated.deprecated_method"}
def deprecated_modules(self):
return {"deprecated_module"}
def deprecated_arguments(self, method):
if method == "myfunction1":
# def myfunction1(arg1, deprecated_arg1='spam')
return ((1, "deprecated_arg1"),)
if method == "myfunction2":
# def myfunction2(arg1, deprecated_arg1, arg2='foo', deprecated_arg2='spam'))
return ((1, "deprecated_arg1"), (3, "deprecated_arg2"))
if method == "myfunction3":
# def myfunction1(arg1, *, deprecated_arg1='spam')
return ((None, "deprecated_arg1"),)
if method == ".MyClass.mymethod1":
# def mymethod1(self, arg1, deprecated_arg1=None)
return ((1, "deprecated_arg1"),)
if method == ".MyClass.mymethod2":
# def mymethod2(self, arg1, deprecated_arg1='bar', arg2='foo', deprecated_arg2='spam'))
return ((1, "deprecated_arg1"), (3, "deprecated_arg2"))
if method == ".MyClass.mymethod3":
# def mymethod1(self, arg1, *, deprecated_arg1=None)
return ((None, "deprecated_arg1"),)
return ()
class TestDeprecatedChecker(CheckerTestCase):
CHECKER_CLASS = _DeprecatedChecker
def test_deprecated_function(self):
# Tests detecting deprecated function
node = astroid.extract_node(
"""
def deprecated_func():
pass
deprecated_func()
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-method",
args=("deprecated_func",),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_deprecated_method(self):
# Tests detecting deprecated method
node = astroid.extract_node(
"""
class Deprecated:
def deprecated_method():
pass
d = Deprecated()
d.deprecated_method()
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-method",
args=("deprecated_method",),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_no_message(self):
# Tests not raising error when no deprecated functions/methods are present.
node = astroid.extract_node(
"""
class MyClass:
def mymethod():
pass
MyClass().mymethod()
def myfunc():
pass
myfunc()
"""
)
with self.assertNoMessages():
self.checker.visit_call(node)
def test_function_deprecated_arg(self):
# Tests raising error when calling function with deprecated argument
node = astroid.extract_node(
"""
def myfunction1(arg1, deprecated_arg1='spam'):
pass
myfunction1(None, 'deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "myfunction1"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_function_deprecated_kwarg(self):
# Tests raising error when calling function with deprecated keyword argument
node = astroid.extract_node(
"""
def myfunction1(arg1, deprecated_arg1='spam'):
pass
myfunction1(None, deprecated_arg1='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "myfunction1"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_function_deprecated_not_used(self):
# Tests raising error when calling function without deprecated argument
node = astroid.extract_node(
"""
def myfunction1(arg1, deprecated_arg1='spam'):
pass
myfunction1(None)
"""
)
with self.assertNoMessages():
self.checker.visit_call(node)
def test_function_deprecated_kwarg_only(self):
# Tests raising error when calling function with deprecated keyword only argument
node = astroid.extract_node(
"""
def myfunction3(arg1, *, deprecated_arg1='spam'):
pass
myfunction3(None, deprecated_arg1='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "myfunction3"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_method_deprecated_arg(self):
# Tests raising error when calling method with deprecated argument
node = astroid.extract_node(
"""
class MyClass:
def mymethod1(self, arg1, deprecated_arg1):
pass
MyClass().mymethod1(None, 'deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "mymethod1"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_method_deprecated_kwarg(self):
# Tests raising error when calling method with deprecated keyword argument
node = astroid.extract_node(
"""
class MyClass:
def mymethod1(self, arg1, deprecated_arg1):
pass
MyClass().mymethod1(None, deprecated_arg1='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "mymethod1"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_method_deprecated_not_used(self):
# Tests raising error when calling method without deprecated argument
node = astroid.extract_node(
"""
class MyClass:
def mymethod1(self, arg1, deprecated_arg1):
pass
MyClass().mymethod1(None)
"""
)
with self.assertNoMessages():
self.checker.visit_call(node)
def test_method_deprecated_kwarg_only(self):
# Tests raising error when calling method with deprecated keyword only argument
node = astroid.extract_node(
"""
class MyClass:
def mymethod3(self, arg1, *, deprecated_arg1):
pass
MyClass().mymethod3(None, deprecated_arg1='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "mymethod3"),
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_call(node)
def test_function_deprecated_arg_kwargs(self):
# Tests raising error when calling function with deprecated argument
# and keyword argument
node = astroid.extract_node(
"""
def myfunction2(arg1, deprecated_arg1, arg2='foo', deprecated_arg2='spam'):
pass
myfunction2(None, 'deprecated', deprecated_arg2='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "myfunction2"),
node=node,
confidence=UNDEFINED,
),
Message(
msg_id="deprecated-argument",
args=("deprecated_arg2", "myfunction2"),
node=node,
confidence=UNDEFINED,
),
):
self.checker.visit_call(node)
def test_function_deprecated_kwarg_kwarg(self):
# Tests raising error when calling function with deprecated keyword arguments
node = astroid.extract_node(
"""
def myfunction2(arg1, deprecated_arg1, arg2='foo', deprecated_arg2='spam'):
pass
myfunction2(None, deprecated_arg1='deprecated', deprecated_arg2='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "myfunction2"),
node=node,
confidence=UNDEFINED,
),
Message(
msg_id="deprecated-argument",
args=("deprecated_arg2", "myfunction2"),
node=node,
confidence=UNDEFINED,
),
):
self.checker.visit_call(node)
def test_method_deprecated_arg_kwargs(self):
# Tests raising error when calling method with deprecated argument
# and keyword argument
node = astroid.extract_node(
"""
class MyClass:
def mymethod2(self, arg1, deprecated_arg1, arg2='foo', deprecated_arg2='spam'):
pass
MyClass().mymethod2(None, 'deprecated', deprecated_arg2='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "mymethod2"),
node=node,
confidence=UNDEFINED,
),
Message(
msg_id="deprecated-argument",
args=("deprecated_arg2", "mymethod2"),
node=node,
confidence=UNDEFINED,
),
):
self.checker.visit_call(node)
def test_method_deprecated_kwarg_kwarg(self):
# Tests raising error when calling method with deprecated keyword arguments
node = astroid.extract_node(
"""
class MyClass:
def mymethod2(self, arg1, deprecated_arg1, arg2='foo', deprecated_arg2='spam'):
pass
MyClass().mymethod2(None, deprecated_arg1='deprecated', deprecated_arg2='deprecated')
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-argument",
args=("deprecated_arg1", "mymethod2"),
node=node,
confidence=UNDEFINED,
),
Message(
msg_id="deprecated-argument",
args=("deprecated_arg2", "mymethod2"),
node=node,
confidence=UNDEFINED,
),
):
self.checker.visit_call(node)
def test_deprecated_module(self):
# Tests detecting deprecated module
node = astroid.extract_node(
"""
import deprecated_module
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-module",
args="deprecated_module",
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_import(node)
def test_deprecated_module_from(self):
# Tests detecting deprecated module
node = astroid.extract_node(
"""
from deprecated_module import myfunction
"""
)
with self.assertAddsMessages(
Message(
msg_id="deprecated-module",
args="deprecated_module",
node=node,
confidence=UNDEFINED,
)
):
self.checker.visit_importfrom(node)
| 31.511392 | 99 | 0.545433 | 1,059 | 12,447 | 6.235127 | 0.07932 | 0.08481 | 0.049069 | 0.059973 | 0.842799 | 0.820536 | 0.802968 | 0.780403 | 0.762078 | 0.719976 | 0 | 0.017103 | 0.361131 | 12,447 | 394 | 100 | 31.591371 | 0.813255 | 0.11786 | 0 | 0.696581 | 0 | 0 | 0.123173 | 0.003475 | 0 | 0 | 0 | 0 | 0.07265 | 1 | 0.08547 | false | 0 | 0.025641 | 0.008547 | 0.17094 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
f9e36b3582bece605a4bf6bf2d22ee6b8cb26b24 | 131 | py | Python | pisat/actuator/bd62xx.py | jjj999/pisat | be96cfcd4a68ece14cb5f8745ab138e3931eb761 | [
"MIT"
] | 1 | 2020-09-23T08:23:47.000Z | 2020-09-23T08:23:47.000Z | pisat/actuator/bd62xx.py | jjj999/pisat | be96cfcd4a68ece14cb5f8745ab138e3931eb761 | [
"MIT"
] | 4 | 2020-07-01T06:31:05.000Z | 2021-05-04T05:53:01.000Z | pisat/actuator/bd62xx.py | jjj999/pisat | be96cfcd4a68ece14cb5f8745ab138e3931eb761 | [
"MIT"
] | 2 | 2020-07-01T06:08:00.000Z | 2020-09-20T00:52:43.000Z |
from pisat.actuator.pwm_dc_motor_driver import PWMDCMotorDriver
class BD62xx(PWMDCMotorDriver):
# same architecture
pass | 18.714286 | 63 | 0.801527 | 15 | 131 | 6.8 | 0.933333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018018 | 0.152672 | 131 | 7 | 64 | 18.714286 | 0.900901 | 0.129771 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 6 |
ddb38390d1e476abbcf87350996444ec403cd61e | 3,467 | py | Python | tests/unit/test_participation.py | EricSchles/crime-data-api | fdc2ec3a151d2c76d43b1dd3bebe56e34aa58757 | [
"CC0-1.0"
] | 51 | 2016-09-16T00:37:56.000Z | 2022-01-22T03:48:24.000Z | tests/unit/test_participation.py | harrisj/crime-data-api | 9b49b5cc3cd8309dda888f49356ee5168c43851a | [
"CC0-1.0"
] | 605 | 2016-09-15T19:16:49.000Z | 2018-01-18T20:46:39.000Z | tests/unit/test_participation.py | harrisj/crime-data-api | 9b49b5cc3cd8309dda888f49356ee5168c43851a | [
"CC0-1.0"
] | 12 | 2018-01-18T21:15:34.000Z | 2022-02-17T10:09:40.000Z | from crime_data.common.newmodels import (AgencyParticipation, ParticipationRate)
import pytest
class TestAgencyParticipation:
def test_for_agency_not_reporting(self, app):
q = AgencyParticipation.query
q = q.filter(AgencyParticipation.year == 2014)
q = q.filter(AgencyParticipation.agency_id == 17380).one()
assert q.reported == 0
assert q.months_reported == 0
assert q.nibrs_reported == 0
assert q.nibrs_months_reported == 0
def test_for_agency_covered_by_another(self, app):
q = AgencyParticipation.query
q = q.filter(AgencyParticipation.year == 2014)
q = q.filter(AgencyParticipation.agency_id == 17391).one()
assert q.reported == 0
assert q.months_reported == 0
assert q.nibrs_reported == 0
assert q.nibrs_months_reported == 0
assert q.covered == 1
assert q.participated == 1
assert q.nibrs_participated == 1
def test_for_agency_in_nibrs_month(self, app):
q = AgencyParticipation.query
q = q.filter(AgencyParticipation.year == 2014)
q = q.filter(AgencyParticipation.agency_id == 17381).one()
assert q.reported == 1
assert q.months_reported == 12
assert q.nibrs_reported == 1
assert q.nibrs_months_reported == 12
def test_for_agency_not_in_nibrs_month(self, app):
q = AgencyParticipation.query
q = q.filter(AgencyParticipation.year == 2014)
q = q.filter(AgencyParticipation.agency_id == 17427).one()
assert q.reported == 1
assert q.months_reported == 12
assert q.nibrs_reported == 0
assert q.nibrs_months_reported == 0
class TestParticipationRate:
def test_for_state_in_year(self, app):
q = ParticipationRate.query
q = q.filter(ParticipationRate.year == 2014)
q = q.filter(ParticipationRate.state_id == 44).one()
assert q.year == 2014
assert q.state_id == 44
assert q.total_agencies == 62
assert q.participating_agencies == 54
assert q.participation_rate == pytest.approx(0.870967742)
assert q.nibrs_participating_agencies == 52
assert q.nibrs_participation_rate == pytest.approx(0.838709677)
def test_for_county_in_year(self, app):
pass
q = ParticipationRate.query
q = q.filter(ParticipationRate.year == 2014)
q = q.filter(ParticipationRate.state_id == 44).one()
assert q.year == 2014
assert q.state_id == 44
assert q.total_agencies == 62
assert q.participating_agencies == 54
assert q.participation_rate == pytest.approx(0.870967742)
assert q.nibrs_participating_agencies == 52
assert q.nibrs_participation_rate == pytest.approx(0.838709677)
def test_for_year(self, app):
q = ParticipationRate.query
q = q.filter(ParticipationRate.year == 2014)
q = q.filter(ParticipationRate.state_id == None)
q = q.filter(ParticipationRate.county_id == None).one()
assert q.year == 2014
assert q.state_id is None
assert q.total_agencies == 64
assert q.participating_agencies == 54
assert q.participation_rate == pytest.approx(0.84375)
assert q.nibrs_participating_agencies == 52
assert q.nibrs_participation_rate == pytest.approx(0.8125)
assert q.total_population == 12142430
assert q.participating_population == 1055173
| 40.788235 | 80 | 0.660802 | 429 | 3,467 | 5.149184 | 0.156177 | 0.133092 | 0.054323 | 0.097782 | 0.794477 | 0.762336 | 0.762336 | 0.762336 | 0.762336 | 0.74785 | 0 | 0.066565 | 0.246034 | 3,467 | 84 | 81 | 41.27381 | 0.7785 | 0 | 0 | 0.618421 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.552632 | 1 | 0.092105 | false | 0.013158 | 0.026316 | 0 | 0.144737 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
ddc163a2dcc61e3e0e8971991c5d27ad2b68f5f7 | 33 | py | Python | masonite/queues/__init__.py | w3x10e8/core | d8f0ca29c2bd5e86d199391fa916ce2f5c9b0f49 | [
"MIT"
] | null | null | null | masonite/queues/__init__.py | w3x10e8/core | d8f0ca29c2bd5e86d199391fa916ce2f5c9b0f49 | [
"MIT"
] | null | null | null | masonite/queues/__init__.py | w3x10e8/core | d8f0ca29c2bd5e86d199391fa916ce2f5c9b0f49 | [
"MIT"
] | null | null | null | from .Queueable import Queueable
| 16.5 | 32 | 0.848485 | 4 | 33 | 7 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121212 | 33 | 1 | 33 | 33 | 0.965517 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
ddf729de7d9f59cf3648567f7cae677abc84b410 | 5,939 | py | Python | centers.py | abhinavrk/Circle-Detection | 6471966cd2e2b891ca850ed2023e8fbab6f2dff8 | [
"MIT"
] | null | null | null | centers.py | abhinavrk/Circle-Detection | 6471966cd2e2b891ca850ed2023e8fbab6f2dff8 | [
"MIT"
] | null | null | null | centers.py | abhinavrk/Circle-Detection | 6471966cd2e2b891ca850ed2023e8fbab6f2dff8 | [
"MIT"
] | null | null | null | import os
import numpy as np
import scipy.optimize as opt
import scipy.spatial.distance as d
import matplotlib.pyplot as plt
'''
Fit to graph ignoring and considering edge effects
Also calculate goodness of fit and store in Results.txt
'''
def logistic(x, mu, s, A):
return A*(1/4.0/s) * np.cosh((x-mu)/2.0/s)**(-2)
def boltzmann(x,a, A):
return A*(2.0/np.pi)**0.5 * (x**2 * np.exp(-x**2/2.0/(a**2)))/a**3
def gumbel(x, mu,b, A):
z = (x-mu)/b
return A*np.exp(-1.0*(z + np.exp(-z)))/b
def hist_data(array, block):
hist, bins = np.histogram(array, bins=block)
width = 0.7 * (bins[1] - bins[0])
center = (bins[:-1] + bins[1:]) / 2
return center, hist
def runner(pathb, pathg, pathl, file, counter):
log_init = (53.7873757895, 20.3443103825, 6140956.95601)
bltz_init = (37.5461720445, 5133049.50192)
limit_x = limit_y = 140
position = np.loadtxt(file, delimiter = ' ')
x = position[:,0]
y = position[:,1]
c = d.pdist(position)
xvals, yvals = hist_data(c, 50) # Get histogram data
# Cure Fit Logistic
popt_log, pcov_log = opt.curve_fit(logistic, xvals, yvals, p0 = log_init)
y_log = logistic(xvals, popt_log[0], popt_log[1], popt_log[2])
y_log_avg = np.sum(y_log)/float(len(y))
SSreg_log = np.sum((y_log_avg - y_log)**2)
SStot_log = np.sum((y_log_avg - yvals)**2)
R2_log = SSreg_log/float(SStot_log)
plt.plot(xvals, yvals)
plt.plot(xvals, y_log)
plt.title('Logistic Fit Graph - R^2 is {0}'.format(R2_log))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathl + 'Logistic{0}.png'.format(counter))
# plt.show()
# Cure Fit Boltzman
popt_b, pcov_b = opt.curve_fit(boltzmann, xvals, yvals, p0= bltz_init)
y_b = boltzmann(xvals, popt_b[0], popt_b[1])
y_b_avg = np.sum(y_b)/float(len(y))
SSreg_b = np.sum((y_b_avg - y_b)**2)
SStot_b = np.sum((y_b_avg - yvals)**2)
R2_b = SSreg_b/float(SStot_b)
plt.close()
plt.plot(xvals, yvals)
plt.plot(xvals, y_log)
plt.title('Boltzmann Fit Graph - R^2 is {0}'.format(R2_b))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathb+'Boltzmann{0}.png'.format(counter))
# Cure Fit Gumbel
popt_g, pcov_g = opt.curve_fit(gumbel, xvals, yvals , p0 = log_init)
y_g = gumbel(xvals, popt_g[0], popt_g[1], popt_g[2])
y_g_avg = np.sum(y_g)/float(len(y))
SSreg_g = np.sum((y_g_avg - y_g)**2)
SStot_g = np.sum((y_g_avg - yvals)**2)
R2_g = SSreg_g/float(SStot_g)
plt.close()
plt.plot(xvals, yvals)
plt.plot(xvals, y_g)
plt.title('Gumbel Fit Graph - R^2 is {0}'.format(R2_g))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathg + 'Gumbel{0}.png'.format(counter))
plt.close()
return R2_b, R2_log, R2_g
def runnermod(pathb, pathg, pathl, file, counter):
log_init = (53.7873757895, 20.3443103825, 6140956.95601)
bltz_init = (37.5461720445, 5133049.50192)
limit_x = limit_y = 140
position = np.loadtxt(file, delimiter = ' ')
x = position[:,0]
y = position[:,1]
c = d.pdist(position)
xvals, yvals = hist_data(c, 50) # Get histogram data
# Cure Fit Logistic
popt_log, pcov_log = opt.curve_fit(logistic, xvals[xvals<95], yvals[xvals<95], p0 = log_init)
y_log = logistic(xvals, popt_log[0], popt_log[1], popt_log[2])
y_log_avg = np.sum(y_log)/float(len(y))
SSreg_log = np.sum((y_log_avg - y_log)**2)
SStot_log = np.sum((y_log_avg - yvals)**2)
R2_log = SSreg_log/float(SStot_log)
plt.plot(xvals, yvals)
plt.plot(xvals, y_log)
plt.title('Logistic Fit Graph - R^2 is {0}'.format(R2_log))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathl + 'Logistic_mod{0}.png'.format(counter))
# plt.show()
# Cure Fit Boltzman
popt_b, pcov_b = opt.curve_fit(boltzmann, xvals[xvals<95], yvals[xvals<95], p0= bltz_init)
y_b = boltzmann(xvals, popt_b[0], popt_b[1])
y_b_avg = np.sum(y_b)/float(len(y))
SSreg_b = np.sum((y_b_avg - y_b)**2)
SStot_b = np.sum((y_b_avg - yvals)**2)
R2_b = SSreg_b/float(SStot_b)
plt.close()
plt.plot(xvals, yvals)
plt.plot(xvals, y_log)
plt.title('Boltzmann Fit Graph - R^2 is {0}'.format(R2_b))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathb+'Boltzmann_mod{0}.png'.format(counter))
# Cure Fit Gumbel
popt_g, pcov_g = opt.curve_fit(gumbel, xvals[xvals<95], yvals[xvals<95] , p0 = log_init)
y_g = gumbel(xvals, popt_g[0], popt_g[1], popt_g[2])
y_g_avg = np.sum(y_g)/float(len(y))
SSreg_g = np.sum((y_g_avg - y_g)**2)
SStot_g = np.sum((y_g_avg - yvals)**2)
R2_g = SSreg_g/float(SStot_g)
plt.close()
plt.plot(xvals, yvals)
plt.plot(xvals, y_g)
plt.title('Gumbel Fit Graph - R^2 is {0}'.format(R2_g))
plt.xlabel('$l$ (in units radius)')
plt.ylabel('Frequency')
plt.savefig(pathg + 'Gumbel_mod{0}.png'.format(counter))
plt.close()
return R2_b, R2_log, R2_g
a = os.listdir("C:\Users\Abhinav\Desktop\AdvPhyLab\checkin3\AdvPhyLab")
pathy = "C:\\Users\\Abhinav\\Desktop\\AdvPhyLab\\checkin3\\pure_data_analysis\\"
bpath = "C:\\Users\\Abhinav\\Desktop\\AdvPhyLab\\checkin3\\pure_data_analysis\\Boltzmann\\"
lpath = "C:\\Users\\Abhinav\\Desktop\\AdvPhyLab\\checkin3\\pure_data_analysis\\Logistic\\"
gpath = "C:\\Users\\Abhinav\\Desktop\\AdvPhyLab\\checkin3\\pure_data_analysis\\Gumbel\\"
filenames = []
for name in a:
if '_centers' in name:
filenames.append(name)
bolt = []
loggy = []
gummy = []
boltm = []
loggym = []
gummym = []
l = 0
for filename in filenames:
R2_b, R2_log, R2_g = runner(bpath, gpath, lpath, pathy+ filename, l)
R2_bm, R2_logm, R2_gm = runnermod(bpath, gpath, lpath, pathy+ filename, l)
bolt.append(R2_b)
loggy.append(R2_log)
gummy.append(R2_g)
boltm.append(R2_bm)
loggym.append(R2_logm)
gummym.append(R2_gm)
l+=1
f = file("Results.txt", 'a')
np.savetxt(f, [bolt, loggy, gummy, boltm, loggym, gummym])
def avg(arr):
return sum(arr)/float(len(arr))
print 'Boltz: ', avg(bolt),'Logist: ', avg(loggy),'Gumbel: ', avg(gummy)
print 'Boltz_mod: ', avg(boltm),'Logist_mod: ', avg(loggym),'Gumbel_mod: ', avg(gummym)
| 28.970732 | 95 | 0.678565 | 1,066 | 5,939 | 3.611632 | 0.146341 | 0.023377 | 0.028052 | 0.014026 | 0.774026 | 0.773247 | 0.725455 | 0.720519 | 0.720519 | 0.665455 | 0 | 0.050653 | 0.135713 | 5,939 | 204 | 96 | 29.112745 | 0.699396 | 0.027446 | 0 | 0.571429 | 0 | 0 | 0.160411 | 0.064093 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.034014 | null | null | 0.013605 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
fb01d0fb61d7cbc6850d32b784441fe7c5ba9d5b | 42,016 | py | Python | tests/models/test_dataset.py | foobarbecue/pyDataverse | b0f73e95a498412e15f26c02e17de3c049c7efb8 | [
"MIT"
] | 21 | 2020-12-29T18:19:26.000Z | 2022-03-19T15:19:01.000Z | tests/models/test_dataset.py | foobarbecue/pyDataverse | b0f73e95a498412e15f26c02e17de3c049c7efb8 | [
"MIT"
] | 92 | 2020-12-09T15:36:59.000Z | 2022-03-22T21:16:10.000Z | tests/models/test_dataset.py | foobarbecue/pyDataverse | b0f73e95a498412e15f26c02e17de3c049c7efb8 | [
"MIT"
] | 19 | 2019-05-06T18:46:05.000Z | 2020-12-07T20:54:52.000Z | """Dataset data model tests."""
import json
import os
import platform
import pytest
from pyDataverse.models import Dataset
from ..conftest import test_config
def read_file(filename, mode="r"):
"""Read in a file.
Parameters
----------
filename : str
Filename with full path.
mode : str
Read mode of file. Defaults to `r`. See more at
https://docs.python.org/3.5/library/functions.html#open
Returns
-------
str
Returns data as string.
"""
with open(filename, mode) as f:
return f.read()
def write_json(filename, data, mode="w", encoding="utf-8"):
"""Write data to a json file.
Parameters
----------
filename : str
Filename with full path.
data : dict
Data to be written in the json file.
mode : str
Write mode of file. Defaults to `w`. See more at
https://docs.python.org/3/library/functions.html#open
"""
with open(filename, mode, encoding=encoding) as f:
json.dump(data, f, indent=2)
def data_object():
"""Get Dataset object.
Returns
-------
pydataverse.models.Dataset
:class:`Dataset` object.
"""
return Dataset()
def dict_flat_set_min():
"""Get flat dict for set() of minimum Dataset.
Returns
-------
dict
Flat dict with minimum Dataset data.
"""
return {
"title": "Darwin's Finches",
"author": [{"authorName": "Finch, Fiona", "authorAffiliation": "Birds Inc."}],
"datasetContact": [
{
"datasetContactEmail": "finch@mailinator.com",
"datasetContactName": "Finch, Fiona",
}
],
"dsDescription": [
{
"dsDescriptionValue": "Darwin's finches (also known as the Galápagos finches) are a group of about fifteen species of passerine birds."
}
],
"subject": ["Medicine, Health and Life Sciences"],
"citation_displayName": "Citation Metadata",
}
def dict_flat_set_full():
"""Get flat dict for set() of full Dataset.
Returns
-------
dict
Flat dict with full Dataset data.
"""
return {
"license": "CC0",
"termsOfUse": "CC0 Waiver",
"termsOfAccess": "Terms of Access",
"fileAccessRequest": True,
"protocol": "doi",
"authority": "10.11587",
"identifier": "6AQBYW",
"citation_displayName": "Citation Metadata",
"title": "Replication Data for: Title",
"subtitle": "Subtitle",
"alternativeTitle": "Alternative Title",
"alternativeURL": "http://AlternativeURL.org",
"otherId": [
{"otherIdAgency": "OtherIDAgency1", "otherIdValue": "OtherIDIdentifier1"}
],
"author": [
{
"authorName": "LastAuthor1, FirstAuthor1",
"authorAffiliation": "AuthorAffiliation1",
"authorIdentifierScheme": "ORCID",
"authorIdentifier": "AuthorIdentifier1",
}
],
"datasetContact": [
{
"datasetContactName": "LastContact1, FirstContact1",
"datasetContactAffiliation": "ContactAffiliation1",
"datasetContactEmail": "ContactEmail1@mailinator.com",
}
],
"dsDescription": [
{
"dsDescriptionValue": "DescriptionText2",
"dsDescriptionDate": "1000-02-02",
}
],
"subject": [
"Agricultural Sciences",
"Business and Management",
"Engineering",
"Law",
],
"keyword": [
{
"keywordValue": "KeywordTerm1",
"keywordVocabulary": "KeywordVocabulary1",
"keywordVocabularyURI": "http://KeywordVocabularyURL1.org",
}
],
"topicClassification": [
{
"topicClassValue": "Topic Class Value1",
"topicClassVocab": "Topic Classification Vocabulary",
"topicClassVocabURI": "https://topic.class/vocab/uri",
}
],
"publication": [
{
"publicationCitation": "RelatedPublicationCitation1",
"publicationIDType": "ark",
"publicationIDNumber": "RelatedPublicationIDNumber1",
"publicationURL": "http://RelatedPublicationURL1.org",
}
],
"notesText": "Notes1",
"producer": [
{
"producerName": "LastProducer1, FirstProducer1",
"producerAffiliation": "ProducerAffiliation1",
"producerAbbreviation": "ProducerAbbreviation1",
"producerURL": "http://ProducerURL1.org",
"producerLogoURL": "http://ProducerLogoURL1.org",
}
],
"productionDate": "1003-01-01",
"productionPlace": "ProductionPlace",
"contributor": [
{
"contributorType": "Data Collector",
"contributorName": "LastContributor1, FirstContributor1",
}
],
"grantNumber": [
{
"grantNumberAgency": "GrantInformationGrantAgency1",
"grantNumberValue": "GrantInformationGrantNumber1",
}
],
"distributor": [
{
"distributorName": "LastDistributor1, FirstDistributor1",
"distributorAffiliation": "DistributorAffiliation1",
"distributorAbbreviation": "DistributorAbbreviation1",
"distributorURL": "http://DistributorURL1.org",
"distributorLogoURL": "http://DistributorLogoURL1.org",
}
],
"distributionDate": "1004-01-01",
"depositor": "LastDepositor, FirstDepositor",
"dateOfDeposit": "1002-01-01",
"timePeriodCovered": [
{
"timePeriodCoveredStart": "1005-01-01",
"timePeriodCoveredEnd": "1005-01-02",
}
],
"dateOfCollection": [
{"dateOfCollectionStart": "1006-01-01", "dateOfCollectionEnd": "1006-01-01"}
],
"kindOfData": ["KindOfData1", "KindOfData2"],
"language": ["German"],
"series": {
"seriesName": "SeriesName",
"seriesInformation": "SeriesInformation",
},
"software": [
{"softwareName": "SoftwareName1", "softwareVersion": "SoftwareVersion1"}
],
"relatedMaterial": ["RelatedMaterial1", "RelatedMaterial2"],
"relatedDatasets": ["RelatedDatasets1", "RelatedDatasets2"],
"otherReferences": ["OtherReferences1", "OtherReferences2"],
"dataSources": ["DataSources1", "DataSources2"],
"originOfSources": "OriginOfSources",
"characteristicOfSources": "CharacteristicOfSourcesNoted",
"accessToSources": "DocumentationAndAccessToSources",
"geospatial_displayName": "Geospatial Metadata",
"geographicCoverage": [
{
"country": "Afghanistan",
"state": "GeographicCoverageStateProvince1",
"city": "GeographicCoverageCity1",
"otherGeographicCoverage": "GeographicCoverageOther1",
}
],
"geographicUnit": ["GeographicUnit1", "GeographicUnit2"],
"geographicBoundingBox": [
{
"westLongitude": "10",
"eastLongitude": "20",
"northLongitude": "30",
"southLongitude": "40",
}
],
"socialscience_displayName": "Social Science and Humanities Metadata",
"unitOfAnalysis": ["UnitOfAnalysis1", "UnitOfAnalysis2"],
"universe": ["Universe1", "Universe2"],
"timeMethod": "TimeMethod",
"dataCollector": "LastDataCollector1, FirstDataCollector1",
"collectorTraining": "CollectorTraining",
"frequencyOfDataCollection": "Frequency",
"samplingProcedure": "SamplingProcedure",
"targetSampleSize": {
"targetSampleActualSize": "100",
"targetSampleSizeFormula": "TargetSampleSizeFormula",
},
"deviationsFromSampleDesign": "MajorDeviationsForSampleDesign",
"collectionMode": "CollectionMode",
"researchInstrument": "TypeOfResearchInstrument",
"dataCollectionSituation": "CharacteristicsOfDataCollectionSituation",
"actionsToMinimizeLoss": "ActionsToMinimizeLosses",
"controlOperations": "ControlOperations",
"weighting": "Weighting",
"cleaningOperations": "CleaningOperations",
"datasetLevelErrorNotes": "StudyLevelErrorNotes",
"responseRate": "ResponseRate",
"samplingErrorEstimates": "EstimatesOfSamplingError",
"otherDataAppraisal": "OtherFormsOfDataAppraisal",
"socialScienceNotes": {
"socialScienceNotesType": "NotesType",
"socialScienceNotesSubject": "NotesSubject",
"socialScienceNotesText": "NotesText",
},
"journal_displayName": "Journal Metadata",
"journalVolumeIssue": [
{
"journalVolume": "JournalVolume1",
"journalIssue": "JournalIssue1",
"journalPubDate": "1008-01-01",
}
],
"journalArticleType": "abstract",
}
def object_data_init():
"""Get dictionary for Dataset with initial attributes.
Returns
-------
dict
Dictionary of init data attributes set.
"""
return {
"_Dataset_default_json_format": "dataverse_upload",
"_Dataset_default_json_schema_filename": test_config[
"dataset_upload_schema_filename"
],
"_Dataset_allowed_json_formats": [
"dataverse_upload",
"dataverse_download",
"dspace",
"custom",
],
"_Dataset_json_dataverse_upload_attr": json_dataverse_upload_attr(),
"_internal_attributes": [],
}
def object_data_min():
"""Get dictionary for Dataset with minimum attributes.
Returns
-------
pyDataverse.Dataset
:class:`Dataset` with minimum attributes set.
"""
return {
"title": "Darwin's Finches",
"author": [{"authorName": "Finch, Fiona", "authorAffiliation": "Birds Inc."}],
"datasetContact": [
{
"datasetContactEmail": "finch@mailinator.com",
"datasetContactName": "Finch, Fiona",
}
],
"dsDescription": [
{
"dsDescriptionValue": "Darwin's finches (also known as the Galápagos finches) are a group of about fifteen species of passerine birds."
}
],
"subject": ["Medicine, Health and Life Sciences"],
"citation_displayName": "Citation Metadata",
}
def object_data_full():
"""Get dictionary for Dataset with full attributes.
Returns
-------
pyDataverse.Dataset
:class:`Dataset` with full attributes set.
"""
return {
"license": "CC0",
"termsOfUse": "CC0 Waiver",
"termsOfAccess": "Terms of Access",
"fileAccessRequest": True,
"protocol": "doi",
"authority": "10.11587",
"identifier": "6AQBYW",
"citation_displayName": "Citation Metadata",
"title": "Replication Data for: Title",
"subtitle": "Subtitle",
"alternativeTitle": "Alternative Title",
"alternativeURL": "http://AlternativeURL.org",
"otherId": [
{"otherIdAgency": "OtherIDAgency1", "otherIdValue": "OtherIDIdentifier1"}
],
"author": [
{
"authorName": "LastAuthor1, FirstAuthor1",
"authorAffiliation": "AuthorAffiliation1",
"authorIdentifierScheme": "ORCID",
"authorIdentifier": "AuthorIdentifier1",
}
],
"datasetContact": [
{
"datasetContactName": "LastContact1, FirstContact1",
"datasetContactAffiliation": "ContactAffiliation1",
"datasetContactEmail": "ContactEmail1@mailinator.com",
}
],
"dsDescription": [
{
"dsDescriptionValue": "DescriptionText2",
"dsDescriptionDate": "1000-02-02",
}
],
"subject": [
"Agricultural Sciences",
"Business and Management",
"Engineering",
"Law",
],
"keyword": [
{
"keywordValue": "KeywordTerm1",
"keywordVocabulary": "KeywordVocabulary1",
"keywordVocabularyURI": "http://KeywordVocabularyURL1.org",
}
],
"topicClassification": [
{
"topicClassValue": "Topic Class Value1",
"topicClassVocab": "Topic Classification Vocabulary",
"topicClassVocabURI": "https://topic.class/vocab/uri",
}
],
"publication": [
{
"publicationCitation": "RelatedPublicationCitation1",
"publicationIDType": "ark",
"publicationIDNumber": "RelatedPublicationIDNumber1",
"publicationURL": "http://RelatedPublicationURL1.org",
}
],
"notesText": "Notes1",
"producer": [
{
"producerName": "LastProducer1, FirstProducer1",
"producerAffiliation": "ProducerAffiliation1",
"producerAbbreviation": "ProducerAbbreviation1",
"producerURL": "http://ProducerURL1.org",
"producerLogoURL": "http://ProducerLogoURL1.org",
}
],
"productionDate": "1003-01-01",
"productionPlace": "ProductionPlace",
"contributor": [
{
"contributorType": "Data Collector",
"contributorName": "LastContributor1, FirstContributor1",
}
],
"grantNumber": [
{
"grantNumberAgency": "GrantInformationGrantAgency1",
"grantNumberValue": "GrantInformationGrantNumber1",
}
],
"distributor": [
{
"distributorName": "LastDistributor1, FirstDistributor1",
"distributorAffiliation": "DistributorAffiliation1",
"distributorAbbreviation": "DistributorAbbreviation1",
"distributorURL": "http://DistributorURL1.org",
"distributorLogoURL": "http://DistributorLogoURL1.org",
}
],
"distributionDate": "1004-01-01",
"depositor": "LastDepositor, FirstDepositor",
"dateOfDeposit": "1002-01-01",
"timePeriodCovered": [
{
"timePeriodCoveredStart": "1005-01-01",
"timePeriodCoveredEnd": "1005-01-02",
}
],
"dateOfCollection": [
{"dateOfCollectionStart": "1006-01-01", "dateOfCollectionEnd": "1006-01-01"}
],
"kindOfData": ["KindOfData1", "KindOfData2"],
"language": ["German"],
"series": {
"seriesName": "SeriesName",
"seriesInformation": "SeriesInformation",
},
"software": [
{"softwareName": "SoftwareName1", "softwareVersion": "SoftwareVersion1"}
],
"relatedMaterial": ["RelatedMaterial1", "RelatedMaterial2"],
"relatedDatasets": ["RelatedDatasets1", "RelatedDatasets2"],
"otherReferences": ["OtherReferences1", "OtherReferences2"],
"dataSources": ["DataSources1", "DataSources2"],
"originOfSources": "OriginOfSources",
"characteristicOfSources": "CharacteristicOfSourcesNoted",
"accessToSources": "DocumentationAndAccessToSources",
"geospatial_displayName": "Geospatial Metadata",
"geographicCoverage": [
{
"country": "Afghanistan",
"state": "GeographicCoverageStateProvince1",
"city": "GeographicCoverageCity1",
"otherGeographicCoverage": "GeographicCoverageOther1",
}
],
"geographicUnit": ["GeographicUnit1", "GeographicUnit2"],
"geographicBoundingBox": [
{
"westLongitude": "10",
"eastLongitude": "20",
"northLongitude": "30",
"southLongitude": "40",
}
],
"socialscience_displayName": "Social Science and Humanities Metadata",
"unitOfAnalysis": ["UnitOfAnalysis1", "UnitOfAnalysis2"],
"universe": ["Universe1", "Universe2"],
"timeMethod": "TimeMethod",
"dataCollector": "LastDataCollector1, FirstDataCollector1",
"collectorTraining": "CollectorTraining",
"frequencyOfDataCollection": "Frequency",
"samplingProcedure": "SamplingProcedure",
"targetSampleSize": {
"targetSampleActualSize": "100",
"targetSampleSizeFormula": "TargetSampleSizeFormula",
},
"deviationsFromSampleDesign": "MajorDeviationsForSampleDesign",
"collectionMode": "CollectionMode",
"researchInstrument": "TypeOfResearchInstrument",
"dataCollectionSituation": "CharacteristicsOfDataCollectionSituation",
"actionsToMinimizeLoss": "ActionsToMinimizeLosses",
"controlOperations": "ControlOperations",
"weighting": "Weighting",
"cleaningOperations": "CleaningOperations",
"datasetLevelErrorNotes": "StudyLevelErrorNotes",
"responseRate": "ResponseRate",
"samplingErrorEstimates": "EstimatesOfSamplingError",
"otherDataAppraisal": "OtherFormsOfDataAppraisal",
"socialScienceNotes": {
"socialScienceNotesType": "NotesType",
"socialScienceNotesSubject": "NotesSubject",
"socialScienceNotesText": "NotesText",
},
"journal_displayName": "Journal Metadata",
"journalVolumeIssue": [
{
"journalVolume": "JournalVolume1",
"journalIssue": "JournalIssue1",
"journalPubDate": "1008-01-01",
}
],
"journalArticleType": "abstract",
}
def dict_flat_get_min():
"""Get flat dict for :func:`get` with minimum data of Dataset.
Returns
-------
dict
Minimum Dataset dictionary returned by :func:`get`.
"""
return {
"title": "Darwin's Finches",
"author": [{"authorName": "Finch, Fiona", "authorAffiliation": "Birds Inc."}],
"datasetContact": [
{
"datasetContactEmail": "finch@mailinator.com",
"datasetContactName": "Finch, Fiona",
}
],
"dsDescription": [
{
"dsDescriptionValue": "Darwin's finches (also known as the Galápagos finches) are a group of about fifteen species of passerine birds."
},
],
"subject": ["Medicine, Health and Life Sciences"],
"citation_displayName": "Citation Metadata",
}
def dict_flat_get_full():
"""Get flat dict for :func:`get` of full data of Dataset.
Returns
-------
dict
Full Datafile dictionary returned by :func:`get`.
"""
return {
"license": "CC0",
"termsOfUse": "CC0 Waiver",
"termsOfAccess": "Terms of Access",
"fileAccessRequest": True,
"protocol": "doi",
"authority": "10.11587",
"identifier": "6AQBYW",
"title": "Replication Data for: Title",
"subtitle": "Subtitle",
"alternativeTitle": "Alternative Title",
"alternativeURL": "http://AlternativeURL.org",
"otherId": [
{"otherIdAgency": "OtherIDAgency1", "otherIdValue": "OtherIDIdentifier1"}
],
"author": [
{
"authorName": "LastAuthor1, FirstAuthor1",
"authorAffiliation": "AuthorAffiliation1",
"authorIdentifierScheme": "ORCID",
"authorIdentifier": "AuthorIdentifier1",
}
],
"datasetContact": [
{
"datasetContactName": "LastContact1, FirstContact1",
"datasetContactAffiliation": "ContactAffiliation1",
"datasetContactEmail": "ContactEmail1@mailinator.com",
}
],
"dsDescription": [
{
"dsDescriptionValue": "DescriptionText2",
"dsDescriptionDate": "1000-02-02",
}
],
"subject": [
"Agricultural Sciences",
"Business and Management",
"Engineering",
"Law",
],
"keyword": [
{
"keywordValue": "KeywordTerm1",
"keywordVocabulary": "KeywordVocabulary1",
"keywordVocabularyURI": "http://KeywordVocabularyURL1.org",
}
],
"topicClassification": [
{
"topicClassValue": "Topic Class Value1",
"topicClassVocab": "Topic Classification Vocabulary",
"topicClassVocabURI": "https://topic.class/vocab/uri",
}
],
"publication": [
{
"publicationCitation": "RelatedPublicationCitation1",
"publicationIDType": "ark",
"publicationIDNumber": "RelatedPublicationIDNumber1",
"publicationURL": "http://RelatedPublicationURL1.org",
}
],
"notesText": "Notes1",
"producer": [
{
"producerName": "LastProducer1, FirstProducer1",
"producerAffiliation": "ProducerAffiliation1",
"producerAbbreviation": "ProducerAbbreviation1",
"producerURL": "http://ProducerURL1.org",
"producerLogoURL": "http://ProducerLogoURL1.org",
}
],
"productionDate": "1003-01-01",
"productionPlace": "ProductionPlace",
"contributor": [
{
"contributorType": "Data Collector",
"contributorName": "LastContributor1, FirstContributor1",
}
],
"grantNumber": [
{
"grantNumberAgency": "GrantInformationGrantAgency1",
"grantNumberValue": "GrantInformationGrantNumber1",
}
],
"distributor": [
{
"distributorName": "LastDistributor1, FirstDistributor1",
"distributorAffiliation": "DistributorAffiliation1",
"distributorAbbreviation": "DistributorAbbreviation1",
"distributorURL": "http://DistributorURL1.org",
"distributorLogoURL": "http://DistributorLogoURL1.org",
}
],
"distributionDate": "1004-01-01",
"depositor": "LastDepositor, FirstDepositor",
"dateOfDeposit": "1002-01-01",
"timePeriodCovered": [
{
"timePeriodCoveredStart": "1005-01-01",
"timePeriodCoveredEnd": "1005-01-02",
}
],
"dateOfCollection": [
{"dateOfCollectionStart": "1006-01-01", "dateOfCollectionEnd": "1006-01-01"}
],
"kindOfData": ["KindOfData1", "KindOfData2"],
"language": ["German"],
"series": {
"seriesName": "SeriesName",
"seriesInformation": "SeriesInformation",
},
"software": [
{"softwareName": "SoftwareName1", "softwareVersion": "SoftwareVersion1"}
],
"relatedMaterial": ["RelatedMaterial1", "RelatedMaterial2"],
"relatedDatasets": ["RelatedDatasets1", "RelatedDatasets2"],
"otherReferences": ["OtherReferences1", "OtherReferences2"],
"dataSources": ["DataSources1", "DataSources2"],
"originOfSources": "OriginOfSources",
"characteristicOfSources": "CharacteristicOfSourcesNoted",
"accessToSources": "DocumentationAndAccessToSources",
"geospatial_displayName": "Geospatial Metadata",
"geographicCoverage": [
{
"country": "Afghanistan",
"state": "GeographicCoverageStateProvince1",
"city": "GeographicCoverageCity1",
"otherGeographicCoverage": "GeographicCoverageOther1",
}
],
"geographicUnit": ["GeographicUnit1", "GeographicUnit2"],
"geographicBoundingBox": [
{
"westLongitude": "10",
"eastLongitude": "20",
"northLongitude": "30",
"southLongitude": "40",
}
],
"socialscience_displayName": "Social Science and Humanities Metadata",
"unitOfAnalysis": ["UnitOfAnalysis1", "UnitOfAnalysis2"],
"universe": ["Universe1", "Universe2"],
"timeMethod": "TimeMethod",
"dataCollector": "LastDataCollector1, FirstDataCollector1",
"collectorTraining": "CollectorTraining",
"frequencyOfDataCollection": "Frequency",
"samplingProcedure": "SamplingProcedure",
"targetSampleSize": {
"targetSampleActualSize": "100",
"targetSampleSizeFormula": "TargetSampleSizeFormula",
},
"deviationsFromSampleDesign": "MajorDeviationsForSampleDesign",
"collectionMode": "CollectionMode",
"researchInstrument": "TypeOfResearchInstrument",
"dataCollectionSituation": "CharacteristicsOfDataCollectionSituation",
"actionsToMinimizeLoss": "ActionsToMinimizeLosses",
"controlOperations": "ControlOperations",
"weighting": "Weighting",
"cleaningOperations": "CleaningOperations",
"datasetLevelErrorNotes": "StudyLevelErrorNotes",
"responseRate": "ResponseRate",
"samplingErrorEstimates": "EstimatesOfSamplingError",
"otherDataAppraisal": "OtherFormsOfDataAppraisal",
"socialScienceNotes": {
"socialScienceNotesType": "NotesType",
"socialScienceNotesSubject": "NotesSubject",
"socialScienceNotesText": "NotesText",
},
"journal_displayName": "Journal Metadata",
"journalVolumeIssue": [
{
"journalVolume": "JournalVolume1",
"journalIssue": "JournalIssue1",
"journalPubDate": "1008-01-01",
}
],
"journalArticleType": "abstract",
"citation_displayName": "Citation Metadata",
}
def json_upload_min():
"""Get JSON string of minimum Dataset.
Returns
-------
str
JSON string.
"""
return read_file(test_config["dataset_upload_min_filename"])
def json_upload_full():
"""Get JSON string of full Dataset.
Returns
-------
str
JSON string.
"""
return read_file(test_config["dataset_upload_full_filename"])
def json_dataverse_upload_attr():
"""List of attributes import or export in format `dataverse_upload`.
Returns
-------
list
List of attributes, which will be used for import and export.
"""
return [
"license",
"termsOfUse",
"termsOfAccess",
"fileAccessRequest",
"protocol",
"authority",
"identifier",
"citation_displayName",
"title",
"subtitle",
"alternativeTitle",
"alternativeURL",
"otherId",
"author",
"datasetContact",
"dsDescription",
"subject",
"keyword",
"topicClassification",
"publication",
"notesText",
"producer",
"productionDate",
"productionPlace",
"contributor",
"grantNumber",
"distributor",
"distributionDate",
"depositor",
"dateOfDeposit",
"timePeriodCovered",
"dateOfCollection",
"kindOfData",
"language",
"series",
"software",
"relatedMaterial",
"relatedDatasets",
"otherReferences",
"dataSources",
"originOfSources",
"characteristicOfSources",
"accessToSources",
"geospatial_displayName",
"geographicCoverage",
"geographicUnit",
"geographicBoundingBox",
"socialscience_displayName",
"unitOfAnalysis",
"universe",
"timeMethod",
"dataCollector",
"collectorTraining",
"frequencyOfDataCollection",
"samplingProcedure",
"targetSampleSize",
"deviationsFromSampleDesign",
"collectionMode",
"researchInstrument",
"dataCollectionSituation",
"actionsToMinimizeLoss",
"controlOperations",
"weighting",
"cleaningOperations",
"datasetLevelErrorNotes",
"responseRate",
"samplingErrorEstimates",
"otherDataAppraisal",
"socialScienceNotes",
"journal_displayName",
"journalVolumeIssue",
"journalArticleType",
]
def json_dataverse_upload_required_attr():
"""List of attributes required for `dataverse_upload` JSON.
Returns
-------
list
List of attributes, which will be used for import and export.
"""
return ["title", "author", "datasetContact", "dsDescription", "subject"]
class TestDatasetGeneric(object):
"""Generic tests for Dataset()."""
def test_dataset_set_and_get_valid(self):
"""Test Dataset.get() with valid data."""
data = [
((dict_flat_set_min(), object_data_min()), dict_flat_get_min()),
((dict_flat_set_full(), object_data_full()), dict_flat_get_full()),
(({}, {}), {}),
]
pdv = data_object()
pdv.set(dict_flat_set_min())
assert isinstance(pdv.get(), dict)
for input, data_eval in data:
pdv = data_object()
pdv.set(input[0])
data = pdv.get()
for key, val in data_eval.items():
assert data[key] == input[1][key] == data_eval[key]
assert len(data) == len(input[1]) == len(data_eval)
def test_dataset_set_invalid(self):
"""Test Dataset.set() with invalid data."""
# invalid data
for data in test_config["invalid_set_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.set(data)
def test_dataset_validate_json_valid(self):
"""Test Dataset.validate_json() with valid data."""
data = [
((dict_flat_set_min(), {}), True),
((dict_flat_set_full(), {}), True),
((dict_flat_set_min(), {"data_format": "dataverse_upload"}), True),
(
(
dict_flat_set_min(),
{
"data_format": "dataverse_upload",
"filename_schema": test_config[
"dataset_upload_schema_filename"
],
},
),
True,
),
(
(
dict_flat_set_min(),
{"filename_schema": test_config["dataset_upload_schema_filename"]},
),
True,
),
]
for input, data_eval in data:
pdv = data_object()
pdv.set(input[0])
assert pdv.validate_json() == data_eval
class TestDatasetSpecific(object):
"""Specific tests for Dataset()."""
def test_dataset_from_json_valid(self):
"""Test Dataset.from_json() with valid data."""
data = [
(({json_upload_min()}, {}), object_data_min()),
(({json_upload_full()}, {}), object_data_full()),
(
({json_upload_min()}, {"data_format": "dataverse_upload"}),
object_data_min(),
),
(({json_upload_min()}, {"validate": False}), object_data_min()),
(
({json_upload_min()}, {"filename_schema": "", "validate": False},),
object_data_min(),
),
(
({json_upload_min()}, {"filename_schema": "wrong", "validate": False},),
object_data_min(),
),
(
(
{json_upload_min()},
{
"filename_schema": test_config[
"dataset_upload_schema_filename"
],
"validate": True,
},
),
object_data_min(),
),
]
for input, data_eval in data:
pdv = data_object()
args = input[0]
kwargs = input[1]
pdv.from_json(*args, **kwargs)
for key, val in data_eval.items():
assert getattr(pdv, key) == data_eval[key]
assert len(pdv.__dict__) - len(object_data_init()) == len(data_eval)
def test_dataset_to_json_valid(self):
"""Test Dataset.json() with valid data."""
data = [
((dict_flat_set_min(), {}), json.loads(json_upload_min())),
((dict_flat_set_full(), {}), json.loads(json_upload_full())),
(
(dict_flat_set_min(), {"data_format": "dataverse_upload"}),
json.loads(json_upload_min()),
),
(
(dict_flat_set_min(), {"validate": False}),
json.loads(json_upload_min()),
),
(
(dict_flat_set_min(), {"filename_schema": "", "validate": False},),
json.loads(json_upload_min()),
),
(
(dict_flat_set_min(), {"filename_schema": "wrong", "validate": False},),
json.loads(json_upload_min()),
),
(
(
dict_flat_set_min(),
{
"filename_schema": test_config[
"dataset_upload_schema_filename"
],
"validate": True,
},
),
json.loads(json_upload_min()),
),
]
pdv = data_object()
pdv.set(dict_flat_set_min())
assert isinstance(pdv.json(), str)
# TODO: recursevily test values of lists and dicts
for input, data_eval in data:
pdv = data_object()
pdv.set(input[0])
kwargs = input[1]
data = json.loads(pdv.json(**kwargs))
assert data
assert isinstance(data, dict)
assert len(data) == len(data_eval)
assert len(data["datasetVersion"]["metadataBlocks"]["citation"]) == len(
data_eval["datasetVersion"]["metadataBlocks"]["citation"]
)
assert len(
data["datasetVersion"]["metadataBlocks"]["citation"]["fields"]
) == len(
data_eval["datasetVersion"]["metadataBlocks"]["citation"]["fields"]
)
def test_dataset_init_valid(self):
"""Test Dataset.__init__() with valid data."""
# specific
data = [
(Dataset(), {}),
(Dataset(dict_flat_set_min()), object_data_min()),
(Dataset(dict_flat_set_full()), object_data_full()),
(Dataset({}), {}),
]
for pdv, data_eval in data:
for key, val in data_eval.items():
assert getattr(pdv, key) == data_eval[key]
assert len(pdv.__dict__) - len(object_data_init()) == len(data_eval)
def test_dataset_init_invalid(self):
"""Test Dataset.init() with invalid data."""
pdv = Dataset()
# invalid data
for data in test_config["invalid_set_types"]:
with pytest.raises(AssertionError):
pdv.set(data)
def test_dataset_from_json_invalid(self):
"""Test Dataset.from_json() with invalid data."""
# invalid data
for data in test_config["invalid_json_data_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.from_json(data, validate=False)
if int(platform.python_version_tuple()[1]) >= 5:
for json_string in test_config["invalid_json_strings"]:
with pytest.raises(json.decoder.JSONDecodeError):
pdv = data_object()
pdv.from_json(json_string, validate=False)
else:
for json_string in test_config["invalid_json_strings"]:
with pytest.raises(ValueError):
pdv = data_object()
pdv.from_json(json_string, validate=False)
# invalid `filename_schema`
for filename_schema in test_config["invalid_filename_strings"]:
with pytest.raises(FileNotFoundError):
pdv = data_object()
pdv.from_json(json_upload_min(), filename_schema=filename_schema)
for filename_schema in test_config["invalid_filename_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.from_json(json_upload_min(), filename_schema=filename_schema)
# invalid `data_format`
for data_format in (
test_config["invalid_data_format_types"]
+ test_config["invalid_data_format_strings"]
):
with pytest.raises(AssertionError):
pdv = data_object()
pdv.from_json(
json_upload_min(), data_format=data_format, validate=False
)
# invalid `validate`
for validate in test_config["invalid_validate_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.from_json(json_upload_min(), validate=validate)
def test_dataset_to_json_invalid(self):
"""Test Dataset.json() with non-valid data."""
# invalid `filename_schema`
for filename_schema in test_config["invalid_filename_strings"]:
with pytest.raises(FileNotFoundError):
obj = data_object()
obj.json(filename_schema=filename_schema)
for filename_schema in test_config["invalid_filename_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.json(filename_schema=filename_schema)
# invalid `data_format`
for data_format in (
test_config["invalid_data_format_types"]
+ test_config["invalid_data_format_strings"]
):
with pytest.raises(AssertionError):
pdv = data_object()
pdv.set(dict_flat_set_min())
pdv.json(data_format=data_format, validate=False)
# invalid `validate`
for validate in test_config["invalid_validate_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.set(dict_flat_set_min())
pdv.json(validate=validate)
def test_dataset_validate_json_invalid(self):
"""Test Dataset.validate_json() with non-valid data."""
# invalid `filename_schema`
for filename_schema in test_config["invalid_filename_strings"]:
with pytest.raises(FileNotFoundError):
pdv = data_object()
pdv.set(dict_flat_set_min())
pdv.validate_json(filename_schema=filename_schema)
for filename_schema in test_config["invalid_filename_types"]:
with pytest.raises(AssertionError):
pdv = data_object()
pdv.set(dict_flat_set_min())
pdv.validate_json(filename_schema=filename_schema)
if not os.environ.get("TRAVIS"):
class TestDatasetSpecificTravisNot(object):
"""Generic tests for Dataset(), not running on Travis (no file-write permissions)."""
def test_dataset_to_json_from_json_valid(self):
"""Test Dataset to JSON from JSON with valid data."""
data = [
(dict_flat_set_min(), {}),
(dict_flat_set_full(), {}),
(dict_flat_set_min(), {"data_format": "dataverse_upload"}),
(dict_flat_set_min(), {"validate": False}),
(dict_flat_set_min(), {"filename_schema": "wrong", "validate": False},),
(
dict_flat_set_min(),
{
"filename_schema": test_config[
"dataset_upload_schema_filename"
],
"validate": True,
},
),
]
for data_set, kwargs_from in data:
kwargs = {}
pdv_start = data_object()
pdv_start.set(data_set)
if "validate" in kwargs_from:
if not kwargs_from["validate"]:
kwargs = {"validate": False}
write_json(
test_config["dataset_json_output_filename"],
json.loads(pdv_start.json(**kwargs)),
)
pdv_end = data_object()
kwargs = kwargs_from
pdv_end.from_json(
read_file(test_config["dataset_json_output_filename"]), **kwargs
)
for key, val in pdv_end.get().items():
assert getattr(pdv_start, key) == getattr(pdv_end, key)
assert len(pdv_start.__dict__) == len(pdv_end.__dict__,)
| 34.89701 | 151 | 0.54296 | 2,882 | 42,016 | 7.734212 | 0.148855 | 0.012921 | 0.014805 | 0.015074 | 0.845671 | 0.816689 | 0.778107 | 0.769134 | 0.757784 | 0.737236 | 0 | 0.016945 | 0.33423 | 42,016 | 1,203 | 152 | 34.926018 | 0.779895 | 0.066927 | 0 | 0.64526 | 0 | 0.003058 | 0.410886 | 0.105035 | 0 | 0 | 0 | 0.000831 | 0.026504 | 1 | 0.025484 | false | 0.003058 | 0.006116 | 0 | 0.04791 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
348e11bbb68f9db68d064e65e4141b61d5eda118 | 178 | py | Python | exampleapp/api/views.py | martinpeck/flask-api-starter | 0599c492f3baca8c0db3a771746e4b99907b2d2f | [
"MIT"
] | null | null | null | exampleapp/api/views.py | martinpeck/flask-api-starter | 0599c492f3baca8c0db3a771746e4b99907b2d2f | [
"MIT"
] | 1 | 2021-04-20T20:00:34.000Z | 2021-04-20T20:00:34.000Z | exampleapp/api/views.py | martinpeck/flask-api-starter | 0599c492f3baca8c0db3a771746e4b99907b2d2f | [
"MIT"
] | null | null | null | from . import api
@api.route('/', methods=['GET'])
def index():
return {'hello': 'world'}
@api.route('/test', methods=['GET'])
def test():
return {'hello': 'testing'} | 16.181818 | 36 | 0.573034 | 22 | 178 | 4.636364 | 0.590909 | 0.156863 | 0.254902 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.162921 | 178 | 11 | 37 | 16.181818 | 0.684564 | 0 | 0 | 0 | 0 | 0 | 0.189944 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | true | 0 | 0.142857 | 0.285714 | 0.714286 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
55117faf6b8f7038e6f017bf75c3131581f305ce | 19,805 | py | Python | tests/schrodinger/test_glide.py | jharrymoore/Icolos | c60cc00c34208ab7011d41d52a74651763673e7a | [
"Apache-2.0"
] | 11 | 2022-01-30T14:36:13.000Z | 2022-03-22T09:40:57.000Z | tests/schrodinger/test_glide.py | jharrymoore/Icolos | c60cc00c34208ab7011d41d52a74651763673e7a | [
"Apache-2.0"
] | 2 | 2022-03-23T07:56:49.000Z | 2022-03-24T12:01:42.000Z | tests/schrodinger/test_glide.py | jharrymoore/Icolos | c60cc00c34208ab7011d41d52a74651763673e7a | [
"Apache-2.0"
] | 8 | 2022-01-28T10:32:31.000Z | 2022-03-22T09:40:59.000Z | import os
import time
import unittest
from icolos.core.workflow_steps.schrodinger.glide import StepGlide
from icolos.utils.enums.step_enums import StepBaseEnum, TokenGuardEnum, StepGlideEnum
from icolos.utils.enums.program_parameters import GlideEnum
from tests.tests_paths import (
PATHS_1UYD,
PATHS_EXAMPLEDATA,
get_1UYD_ligands_as_Compounds,
)
from icolos.utils.general.files_paths import attach_root_path
_SBE = StepBaseEnum
_SGE = StepGlideEnum()
_EE = GlideEnum()
_TE = TokenGuardEnum()
class Test_Glide(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls._test_dir = attach_root_path("tests/junk/Glide")
if not os.path.isdir(cls._test_dir):
os.makedirs(cls._test_dir)
def setUp(self):
self._1UYD_compounds = get_1UYD_ligands_as_Compounds(
abs_path=PATHS_1UYD.LIGANDS
)
self.receptor_path = PATHS_1UYD.GRID_PATH
self.receptor_constraints_path = PATHS_1UYD.GRID_CONSTRAINTS_PATH
@classmethod
def tearDownClass(cls):
pass
def test_Glide_run(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {
_SBE.EXEC_PARALLELIZATION_CORES: 4,
_SBE.EXEC_PARALLELIZATION_MAXLENSUBLIST: 2,
},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
}
},
},
}
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = self._1UYD_compounds
glide_step.execute()
self.assertEqual(len(glide_step.get_compounds()), 15)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
self.assertListEqual(
list(
glide_step.get_compounds()[14][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-2.1655, 12.4809, 24.137],
)
self.assertEqual(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetProp(_SBE.ANNOTATION_TAG_DOCKING_SCORE),
"-8.4349",
)
self.assertEqual(
glide_step.get_compounds()[0][0][1]
.get_molecule()
.GetProp(_SBE.ANNOTATION_TAG_DOCKING_SCORE),
"-7.83118",
)
self.assertEqual(
glide_step.get_compounds()[0][0][2]
.get_molecule()
.GetProp(_SBE.ANNOTATION_TAG_DOCKING_SCORE),
"-6.0089",
)
# check SDF write-out
out_path = os.path.join(self._test_dir, "glide_docked.sdf")
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 209000)
def test_Glide_run_parallelization_1core_singleton(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {
_SBE.EXEC_PARALLELIZATION_CORES: 1,
_SBE.EXEC_PARALLELIZATION_MAXLENSUBLIST: 1,
},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
}
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
# execute on one core and put all in one list
time_difference = time.time()
glide_step.execute()
time_difference = time.time() - time_difference
self.assertGreater(time_difference, 100)
self.assertGreater(325, time_difference)
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_single_core_singleton_list.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 50500)
def test_Glide_run_1_core(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 1},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
}
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
# execute on one core and put all in one list
time_difference = time.time()
glide_step.execute()
time_difference = time.time() - time_difference
self.assertGreater(325, time_difference)
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_merged_list_3compounds.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 50500)
def test_Glide_run_parallelization_4cores(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 4},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
}
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
# execute and put all in one list
time_difference = time.time()
glide_step.execute()
time_difference = time.time() - time_difference
self.assertGreater(150, time_difference)
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_parallelized_3compounds.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 50500)
def test_Glide_run_parallelization_4cores_in_file_usage(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 4},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_constraints_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
},
_SGE.MAESTRO_IN_FILE: {
_SGE.MAESTRO_IN_FILE_PATH: PATHS_EXAMPLEDATA.GLIDE_EXAMPLE_IN
},
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
glide_step.execute()
# execute on one core and put all in one list
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
# would be [-2.5618, 10.8202, 25.2644] without constraints
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[3.1229, 4.5141, 24.8603],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_parallelized_3compounds.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 50500)
def test_Glide_run_parallelization_4cores_ensemble_docking(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 4},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [
self.receptor_constraints_path,
self.receptor_path,
],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_LIGANDLIB,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
},
_SBE.GRID_IDS: ["mygrid1", "mygrid2"],
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
# execute on one core and put all in one list
glide_step.execute()
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 6)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][5]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.6072, 10.8798, 24.1289],
)
self.assertListEqual(
["mygrid2", "mygrid2", "mygrid1", "mygrid1", "mygrid1", "mygrid2"],
[
comp.get_molecule().GetProp(_SBE.ANNOTATION_GRID_ID)
for comp in list(glide_step.get_compounds()[0][0])
],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_parallelized_ensemble_docking.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 80000)
def test_Glide_run_parallelization_poseviewer(self):
step_conf = {
_SBE.STEPID: "01_glide",
_SBE.STEP_TYPE: _SBE.STEP_GLIDE,
_SBE.EXEC: {
_SBE.EXEC_PREFIXEXECUTION: "module load schrodinger/2021-2-js-aws",
_SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 4},
_SBE.EXEC_FAILUREPOLICY: {_SBE.EXEC_FAILUREPOLICY_NTRIES: 1},
},
_SBE.SETTINGS: {
_SBE.SETTINGS_ARGUMENTS: {
_SBE.SETTINGS_ARGUMENTS_FLAGS: [],
_SBE.SETTINGS_ARGUMENTS_PARAMETERS: {_EE.GLIDE_HOST: "cpu-only"},
},
_SBE.SETTINGS_ADDITIONAL: {
_SGE.CONFIGURATION: {
_EE.GLIDE_AMIDE_MODE: "trans",
_EE.GLIDE_EXPANDED_SAMPLING: "True",
_EE.GLIDE_GRIDFILE: [self.receptor_path],
_EE.GLIDE_NENHANCED_SAMPLING: "1",
_EE.GLIDE_POSE_OUTTYPE: _EE.GLIDE_POSE_OUTTYPE_POSEVIEWER,
_EE.GLIDE_POSES_PER_LIG: "3",
_EE.GLIDE_POSTDOCK_NPOSE: "25",
_EE.GLIDE_POSTDOCKSTRAIN: "True",
_EE.GLIDE_PRECISION: "SP",
_EE.GLIDE_REWARD_INTRA_HBONDS: "True",
}
},
},
}
compounds = self._1UYD_compounds[:3]
glide_step = StepGlide(**step_conf)
glide_step.data.compounds = compounds
# execute on one core and put all in one list
glide_step.execute()
self.assertEqual(len(glide_step.get_compounds()), 3)
self.assertEqual(len(glide_step.get_compounds()[0][0].get_conformers()), 3)
self.assertListEqual(
list(
glide_step.get_compounds()[0][0][0]
.get_molecule()
.GetConformer(0)
.GetPositions()[0]
),
[-1.5198, 11.3439, 24.0245],
)
# check SDF write-out
out_path = os.path.join(
self._test_dir, "glide_docked_parallelized_3compounds_pv.sdf"
)
glide_step.write_conformers(out_path)
stat_inf = os.stat(out_path)
self.assertGreater(stat_inf.st_size, 50500)
| 38.757339 | 85 | 0.536834 | 1,962 | 19,805 | 5.006626 | 0.102956 | 0.05986 | 0.032984 | 0.057722 | 0.875191 | 0.860837 | 0.860837 | 0.85422 | 0.828057 | 0.819403 | 0 | 0.035646 | 0.365413 | 19,805 | 510 | 86 | 38.833333 | 0.745942 | 0.022621 | 0 | 0.691796 | 0 | 0 | 0.046169 | 0.022025 | 0 | 0 | 0 | 0 | 0.084257 | 1 | 0.022173 | false | 0.002217 | 0.017738 | 0 | 0.042129 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
9b3e9d455874392b39b9a8a367b09175a4b23264 | 21,059 | py | Python | input_generation.py | bobelly/MA_MLforKIMMDY | 33839e004d4303d85095144a33d1f7d28bfa9c19 | [
"MIT"
] | null | null | null | input_generation.py | bobelly/MA_MLforKIMMDY | 33839e004d4303d85095144a33d1f7d28bfa9c19 | [
"MIT"
] | null | null | null | input_generation.py | bobelly/MA_MLforKIMMDY | 33839e004d4303d85095144a33d1f7d28bfa9c19 | [
"MIT"
] | 1 | 2021-10-18T07:26:46.000Z | 2021-10-18T07:26:46.000Z | from numpy.core.numeric import outer
import tensorflow as tf
import os
import numpy as np
import kgcnn
from kgcnn.utils.adj import coordinates_to_distancematrix,define_adjacency_from_distance, distance_to_gauss_basis, get_angle_indices, sort_edge_indices
from kgcnn.utils.data import save_pickle_file,load_pickle_file, ragged_tensor_from_nested_numpy
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from ase.io import read
from utils import get_distance
def generate_input_data(input_dir, output_dir):
"""
Generates nodes, edges, coordinates and distances lists from .pdb files
Args:
input_dir (str): direction for the .pdb files
output_dir (str): output direction
"""
search_path = input_dir
filelist = [f for f in os.listdir(search_path) if os.path.isfile(os.path.join(search_path, f))]
base_list = [x.split(".")[0].split("_")[0] + "_" + x.split(".")[0].split("_")[1] for x in filelist]
base_set = sorted(set(base_list))
all_nodes = []
all_edges = []
all_labels = []
all_atoms = []
for x in base_set:
mol1 = read(search_path+x+"_1.pdb")
an1 = mol1.get_atomic_numbers()
n_1 = mol1.get_global_number_of_atoms()
pos1 = mol1.positions
mol2 = read(search_path+x+"_2.pdb")
n_2 = mol2.get_global_number_of_atoms()
an2 = mol2.get_atomic_numbers()
pos2 = mol2.positions
nodes1 = np.concatenate((np.array([0]),an1),axis=0)
edges1 = np.concatenate((np.array([pos2[0]]),pos1),axis=0)
nodes2 = np.concatenate((np.array([0]),an2),axis=0)
edges2 = np.concatenate((np.array([pos1[0]]),pos2),axis=0)
arr = np.load(search_path+x+".npz", allow_pickle=True)
arr = np.expand_dims(arr[arr.files[0]], axis=0)[0]
if 'e_max' in arr and 'e_00' in arr and 'e_10' in arr:
lab1 = arr['e_max'] - arr['e_00']
lab2 = arr['e_max'] - arr['e_10']
all_labels.append(lab1)
all_labels.append(lab2)
all_nodes.append(nodes1)
all_nodes.append(nodes2)
all_edges.append(edges1)
all_edges.append(edges2)
all_atoms.append(n_1)
all_atoms.append(n_2)
dist = [coordinates_to_distancematrix(x) for x in all_edges]
adj = [define_adjacency_from_distance(x,max_distance=8, max_neighbours=25)[0] for x in dist]
edge_indices = [define_adjacency_from_distance(x,max_distance=8, max_neighbours=25)[1] for x in dist]
edge_dist = [distance_to_gauss_basis(dist[i][adj[i]], bins=40, distance=8, sigma=0.4) for i in range(len(adj))]
save_pickle_file(all_edges, output_dir + "cr_coord.pickle")
save_pickle_file(all_nodes, output_dir + "cr_nodes.pickle",)
save_pickle_file(edge_dist, output_dir + "cr_edges.pickle",)
save_pickle_file(edge_indices, output_dir + "cr_indices.pickle")
np.save(output_dir + "cr_atoms.npy", all_atoms)
np.save(output_dir + "cr_labels.npy",all_labels)
def generate_input_data_cutoff(input_dir, output_dir, cutoff_dist):
"""
Generates nodes, edges, coordinates and distances lists from .pdb files with a cutoff distance
Args:
input_dir (str): direction for the .pdb files
output_dir (str): output direction
cutoff_dist (int): distance for cutoff (in Angsroem)
"""
search_path = input_dir
filelist = [f for f in os.listdir(search_path) if os.path.isfile(os.path.join(search_path, f))]
base_list = [x.split(".")[0].split("_")[0] + "_" + x.split(".")[0].split("_")[1] for x in filelist]
base_set = sorted(set(base_list))
threshold = cutoff_dist
all_nodes = []
all_edges = []
all_labels = []
all_atoms = []
all_nodes_high = []
all_edges_high = []
all_labels_high = []
all_atoms_high = []
for x in base_set:
mol1 = read(search_path+x+"_1.pdb")
an1 = mol1.get_atomic_numbers()
pos1 = mol1.positions
n_1 = mol1.get_global_number_of_atoms()
mol2 = read(search_path+x+"_2.pdb")
an2 = mol2.get_atomic_numbers()
pos2 = mol2.positions
n_2 = mol2.get_global_number_of_atoms()
nodes1 = np.concatenate((np.array([0]),an1),axis=0)
edges1 = np.concatenate((np.array([pos2[0]]),pos1),axis=0)
nodes2 = np.concatenate((np.array([0]),an2),axis=0)
edges2 = np.concatenate((np.array([pos1[0]]),pos2),axis=0)
dist = get_distance(edges1[0,:], edges2[0,:])
arr = np.load(search_path+x+".npz", allow_pickle=True)
arr = np.expand_dims(arr[arr.files[0]], axis=0)[0]
if 'e_max' in arr and 'e_00' in arr and 'e_10' in arr:
lab1 = arr['e_max'] - arr['e_00']
lab2 = arr['e_max'] - arr['e_10']
if dist < threshold:
all_labels.append(lab1)
all_labels.append(lab2)
all_nodes.append(nodes1)
all_nodes.append(nodes2)
all_edges.append(edges1)
all_edges.append(edges2)
all_atoms.append(n_1)
all_atoms.append(n_2)
else:
all_nodes_high.append(nodes1)
all_nodes_high.append(nodes2)
all_labels_high.append(lab1)
all_labels_high.append(lab2)
all_edges_high.append(edges1)
all_edges_high.append(edges2)
all_atoms_high.append(n_1)
all_atoms_high.append(n_2)
dist = [coordinates_to_distancematrix(x) for x in all_edges]
adj = [define_adjacency_from_distance(x,max_distance=3, max_neighbours=25)[0] for x in dist]
edge_indices = [define_adjacency_from_distance(x,max_distance=3, max_neighbours=25)[1] for x in dist]
edge_dist = [distance_to_gauss_basis(dist[i][adj[i]], bins=40, distance=8, sigma=0.4) for i in range(len(adj))]
dist = [coordinates_to_distancematrix(x) for x in all_edges_high]
adj = [define_adjacency_from_distance(x,max_distance=3, max_neighbours=25)[0] for x in dist]
edge_indices_high = [define_adjacency_from_distance(x,max_distance=3, max_neighbours=25)[1] for x in dist]
edge_dist_high = [distance_to_gauss_basis(dist[i][adj[i]], bins=40, distance=8, sigma=0.4) for i in range(len(adj))]
save_pickle_file(all_edges, output_dir+str(cutoff_dist)+"_low_cr_coord.pickle")
save_pickle_file(all_nodes, output_dir+str(cutoff_dist)+"_low_cr_nodes.pickle",)
save_pickle_file(edge_dist, output_dir+str(cutoff_dist)+"_low_cr_edges.pickle",)
save_pickle_file(edge_indices, output_dir+str(cutoff_dist)+"_low_cr_indices.pickle")
np.save(output_dir+str(cutoff_dist)+"_low_cr_labels.npy",all_labels)
np.save(output_dir+str(cutoff_dist)+"_low_cr_atoms.npy",all_atoms)
save_pickle_file(all_edges_high, output_dir+str(cutoff_dist)+"_high_cr_coord.pickle")
save_pickle_file(all_nodes_high, output_dir+str(cutoff_dist)+"_high_cr_nodes.pickle",)
save_pickle_file(edge_dist_high, output_dir+str(cutoff_dist)+"_high_cr_edges.pickle",)
save_pickle_file(edge_indices_high, output_dir+str(cutoff_dist)+"_high_cr_indices.pickle")
np.save(output_dir+str(cutoff_dist)+"_high_cr_labels.npy",all_labels_high)
np.save(output_dir+str(cutoff_dist)+"_high_cr_atoms.npy",all_atoms_high)
def painn_dataset(input_dir, split_size):
"""Creates PaiNN graph input
Args:
input_dir (str): input direction with files created using generate_input_data function
split_size (int): test size
Return:
xtrain (ragged tensor): training data
xtest (ragged tensor): test data
xval (ragged tensor): validation data
ytrain (ragged tensor): training labels
ytest (ragged tensor): test labels
yval (ragged tensor): validation labels
scaler: scaler config for later rescaling of the data
"""
# load Dataset
y_data = np.expand_dims(np.load(input_dir+"cr_labels.npy"),axis=-1)
nodes = load_pickle_file(input_dir+"cr_nodes.pickle")
coord = load_pickle_file(input_dir+"cr_coord.pickle")
equivariant = [np.zeros((len(x), 128, 3)) for x in nodes]
dist = [coordinates_to_distancematrix(x) for x in coord]
edge_indices = [define_adjacency_from_distance(x, max_distance=5, max_neighbours=25)[1] for x in dist]
edge_indices = [x if x[0,1]==1 else sort_edge_indices(np.concatenate([np.array([[0, 1], [1,0]]), x], axis=0)) for x in edge_indices]
del dist # Frees some memory
# Should check again the data function to ensure that radical and hydrogen are on top an edge between them exists.
radical_node_index = [np.array([[0, 1]]) for _ in edge_indices]
radical_edge_index = [np.array([[0]]) for _ in radical_node_index]
scaler = StandardScaler(copy=True)
labels = scaler.fit_transform(y_data)
# Train Test split
labels_new, labels_val, nodes_new, nodes_val, equi_new, equi_val, coord_new, coord_val, \
edge_indices_new, edge_indices_val, radical_node_index_new, radical_node_index_val, radical_edge_index_new, radical_edge_index_val= train_test_split(labels,
nodes, equivariant, coord, edge_indices, radical_node_index, radical_edge_index, test_size=split_size)
del labels, nodes, equivariant, coord, edge_indices, radical_node_index , radical_edge_index,
# Train Test split
labels_train, labels_test, nodes_train, nodes_test, equi_train, equi_test, coord_train, coord_test, \
edge_indices_train, edge_indices_test, radical_node_index_train, radical_node_index_test, radical_edge_index_train, \
radical_edge_index_test= train_test_split( labels_new,
nodes_new, equi_new, coord_new, edge_indices_new, radical_node_index_new, radical_edge_index_new, test_size=split_size)
del labels_new, nodes_new, equi_new, coord_new, edge_indices_new
# Convert to tf.RaggedTensor or tf.tensor
# a copy of the data is generated by ragged_tensor_from_nested_numpy()
nodes_train, equi_train, coord_train, edge_indices_train, radical_node_index_train, radical_edge_index_train = ragged_tensor_from_nested_numpy(
nodes_train), ragged_tensor_from_nested_numpy(equi_train), ragged_tensor_from_nested_numpy(coord_train), ragged_tensor_from_nested_numpy(
edge_indices_train), ragged_tensor_from_nested_numpy(radical_node_index_train), ragged_tensor_from_nested_numpy(radical_edge_index_train)
nodes_test, equi_test, coord_test, edge_indices_test, radical_node_index_test, radical_edge_index_test = ragged_tensor_from_nested_numpy(
nodes_test), ragged_tensor_from_nested_numpy(equi_test), ragged_tensor_from_nested_numpy(coord_test), ragged_tensor_from_nested_numpy(
edge_indices_test), ragged_tensor_from_nested_numpy(radical_node_index_test), ragged_tensor_from_nested_numpy(radical_edge_index_test)
nodes_val, equi_val, coord_val, edge_indices_val, radical_node_index_val, radical_edge_index_val = ragged_tensor_from_nested_numpy(
nodes_val), ragged_tensor_from_nested_numpy(equi_val), ragged_tensor_from_nested_numpy(coord_val), ragged_tensor_from_nested_numpy(
edge_indices_val), ragged_tensor_from_nested_numpy(radical_node_index_val), ragged_tensor_from_nested_numpy(radical_edge_index_val)
# Define input and output data
xtrain = nodes_train, equi_train, coord_train, edge_indices_train, radical_node_index_train, radical_edge_index_train
xtest = nodes_test, equi_test, coord_test, edge_indices_test, radical_node_index_test, radical_edge_index_test
ytrain = labels_train
ytest = labels_test
xval = nodes_val, equi_val, coord_val, edge_indices_val, radical_node_index_val, radical_edge_index_val
yval = labels_val
return(xtrain, xtest, xval, ytrain, ytest, yval, scaler)
def schnet_dataset(input_dir, split_size):
"""
Creates Schnet graph input
Args:
input_dir (str): input direction with files created using generate_input_data function
split_size (int): test size
Return:
xtrain (ragged tensor): training data
xtest (ragged tensor): test data
xval (ragged tensor): validation data
ytrain (ragged tensor): training labels
ytest (ragged tensor): test labels
yval (ragged tensor): validation labels
scaler: scaler config for later rescaling of the data
"""
y_data = np.expand_dims(np.load(input_dir+"cr_labels.npy"),axis=-1)
nodes = load_pickle_file(input_dir+'cr_nodes.pickle')
edges = load_pickle_file(input_dir+"cr_edges.pickle")
edge_indices = load_pickle_file(input_dir+"cr_indices.pickle")
radical_node_index = [np.expand_dims(x[0],axis=0) for x in edge_indices]
radical_edge_index = [np.array([[0]]) for _ in radical_node_index]
scaler = StandardScaler(copy=True)
labels = scaler.fit_transform(y_data)
# Train Test split
labels_train, labels_test, nodes_train, nodes_test, edges_train, edges_test, edge_indices_train, edge_indices_test, \
radical_node_index_train, radical_node_index_test, radical_edge_index_train, radical_edge_index_test = train_test_split(
labels, nodes, edges, edge_indices, radical_node_index, radical_edge_index, test_size=split_size)
del labels, nodes, edges, edge_indices, radical_node_index, radical_edge_index # Free memory after split, if possible
# Convert to tf.RaggedTensor or tf.tensor
# a copy of the data is generated by ragged_tensor_from_nested_numpy()
nodes_train, edges_train, edge_indices_train, radical_node_index_train, radical_edge_index_train = ragged_tensor_from_nested_numpy(
nodes_train), ragged_tensor_from_nested_numpy(edges_train), ragged_tensor_from_nested_numpy(
edge_indices_train), ragged_tensor_from_nested_numpy(radical_node_index_train), ragged_tensor_from_nested_numpy(radical_edge_index_train)
nodes_test, edges_test, edge_indices_test, radical_node_index_test, radical_edge_index_test = ragged_tensor_from_nested_numpy(
nodes_test), ragged_tensor_from_nested_numpy(edges_test), ragged_tensor_from_nested_numpy(
edge_indices_test), ragged_tensor_from_nested_numpy(radical_node_index_test), ragged_tensor_from_nested_numpy(radical_edge_index_test)
# Define input and output data
xtrain = nodes_train, edges_train, edge_indices_train, radical_node_index_train, radical_edge_index_train
xval = nodes_test, edges_test, edge_indices_test, radical_node_index_test, radical_edge_index_test
ytrain = labels_train
yval = labels_test
return(xtrain,xval,ytrain,yval,scaler)
def megnet_dataset(input_dir, split_size):
"""
Creates MegNet graph input
Args:
input_dir (str): input direction with files created using generate_input_data function
split_size (int): test size
Return:
xtrain (ragged tensor): training data
xtest (ragged tensor): test data
xval (ragged tensor): validation data
ytrain (ragged tensor): training labels
ytest (ragged tensor): test labels
yval (ragged tensor): validation labels
scaler: scaler config for later rescaling of the data
"""
y_data = np.expand_dims(np.load(input_dir+"cr_labels.npy"),axis=-1)
nodes = load_pickle_file(input_dir+"cr_nodes.pickle")
edges = load_pickle_file(input_dir+"cr_edges.pickle")
edge_indices = load_pickle_file(input_dir+"cr_indices.pickle")
atoms = np.expand_dims(np.load(input_dir+"cr_atoms.npy"), axis=-1)
radical_node_index = [np.array([[0, 1]]) for _ in edge_indices]
radical_edge_index = [np.array([[0]]) for _ in radical_node_index]
scaler = StandardScaler(copy=True)
labels = scaler.fit_transform(y_data)
# Train Test split
labels_train, labels_test, nodes_train, nodes_test, edges_train, edges_test, edge_indices_train, edge_indices_test, \
atoms_train, atoms_test, radical_node_index_train, radical_node_index_test, radical_edge_index_train, \
radical_edge_index_test = train_test_split(
labels, nodes, edges, edge_indices, atoms, radical_node_index, radical_edge_index, test_size=split_size)
del labels, nodes, edges, edge_indices, atoms, radical_node_index, radical_edge_index # Free memory after split, if possible
# Convert to tf.RaggedTensor or tf.tensor
# a copy of the data is generated by ragged_tensor_from_nested_numpy()
nodes_train, edges_train, edge_indices_train, atoms_train, radical_node_index_train, radical_edge_index_train = ragged_tensor_from_nested_numpy(
nodes_train), ragged_tensor_from_nested_numpy(edges_train), ragged_tensor_from_nested_numpy(
edge_indices_train), tf.constant(atoms_train), ragged_tensor_from_nested_numpy(
radical_node_index_train), ragged_tensor_from_nested_numpy(radical_edge_index_train)
nodes_test, edges_test, edge_indices_test, atoms_test, radical_node_index_test, radical_edge_index_test = ragged_tensor_from_nested_numpy(
nodes_test), ragged_tensor_from_nested_numpy(edges_test), ragged_tensor_from_nested_numpy(
edge_indices_test), tf.constant(atoms_test), ragged_tensor_from_nested_numpy(
radical_node_index_test), ragged_tensor_from_nested_numpy(radical_edge_index_test)
# Define input and output data
xtrain = nodes_train, edges_train, edge_indices_train, atoms_train, radical_node_index_train, radical_edge_index_train
xval = nodes_test, edges_test, edge_indices_test, atoms_test, radical_node_index_test, radical_edge_index_test
ytrain = labels_train
yval = labels_test
return(xtrain,xval,ytrain,yval,scaler)
def dimenet_dataset(input_dir, split_size):
"""
Creates DimeNet++ graph input
Args:
input_dir (str): input direction with files created using generate_input_data function
split_size (int): test size
Return:
xtrain (ragged tensor): training data
xtest (ragged tensor): test data
xval (ragged tensor): validation data
ytrain (ragged tensor): training labels
ytest (ragged tensor): test labels
yval (ragged tensor): validation labels
scaler: scaler config for later rescaling of the data
"""
y_data = np.expand_dims(np.load(input_dir+"cr_labels.npy"), axis=-1)
nodes = load_pickle_file(input_dir+"cr_nodes.pickle")
coord = load_pickle_file(input_dir+"cr_coord.pickle")
dist = [coordinates_to_distancematrix(x) for x in coord]
edge_indices = [define_adjacency_from_distance(x, max_distance=5, max_neighbours=25)[1] for x in dist]
edge_indices = [x if x[0,1]==1 else sort_edge_indices(np.concatenate([np.array([[0, 1], [1,0]]), x], axis=0)) for x in edge_indices]
angle_indices = [get_angle_indices(x, is_sorted=True)[2] for x in edge_indices]
del dist # Frees some memory
radical_node_index = [np.array([[0, 1]]) for _ in edge_indices] # für Kohlenstoff
radical_edge_index = [np.array([[0]]) for _ in radical_node_index]
scaler = StandardScaler(copy=True)
labels = scaler.fit_transform(y_data)
# Train Test split
labels_train, labels_test, nodes_train, nodes_test, coord_train, coord_test, edge_indices_train, edge_indices_test, \
angle_indices_train, angle_indices_test, \
radical_node_index_train, radical_node_index_test, radical_edge_index_train, radical_edge_index_test = train_test_split(
labels, nodes, coord, edge_indices, angle_indices, radical_node_index, radical_edge_index, test_size=split_size)
del labels, nodes, coord, edge_indices, angle_indices, radical_node_index, radical_edge_index # Free memory after split, if possible
# Convert to tf.RaggedTensor or tf.tensor
# a copy of the data is generated by ragged_tensor_from_nested_numpy()
nodes_train, coord_train, edge_indices_train, angle_indices_train, radical_node_index_train, radical_edge_index_train = ragged_tensor_from_nested_numpy(
nodes_train), ragged_tensor_from_nested_numpy(coord_train), ragged_tensor_from_nested_numpy(
edge_indices_train), ragged_tensor_from_nested_numpy(angle_indices_train), ragged_tensor_from_nested_numpy(
radical_node_index_train), ragged_tensor_from_nested_numpy(radical_edge_index_train)
nodes_test, coord_test, edge_indices_test, angle_indices_test, radical_node_index_test, radical_edge_index_test = ragged_tensor_from_nested_numpy(
nodes_test), ragged_tensor_from_nested_numpy(coord_test), ragged_tensor_from_nested_numpy(
edge_indices_test), ragged_tensor_from_nested_numpy(angle_indices_test), ragged_tensor_from_nested_numpy(
radical_node_index_test), ragged_tensor_from_nested_numpy(radical_edge_index_test)
# Define input and output data
xtrain = nodes_train, coord_train, edge_indices_train, angle_indices_train, radical_node_index_train, radical_edge_index_train
xval = nodes_test, coord_test, edge_indices_test, angle_indices_test, radical_node_index_test, radical_edge_index_test
ytrain = labels_train
yval = labels_test
return(xtrain,xval,ytrain,yval,scaler)
| 53.04534 | 164 | 0.735363 | 3,112 | 21,059 | 4.579692 | 0.066838 | 0.066517 | 0.061746 | 0.0849 | 0.903873 | 0.883315 | 0.864791 | 0.846197 | 0.801993 | 0.79652 | 0 | 0.012349 | 0.173275 | 21,059 | 396 | 165 | 53.179293 | 0.806261 | 0.154091 | 0 | 0.548387 | 0 | 0 | 0.03709 | 0.006172 | 0 | 0 | 0 | 0 | 0 | 1 | 0.024194 | false | 0 | 0.044355 | 0 | 0.068548 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
9b66594e6489bb03a311a2f1256d7548d19797f9 | 31 | py | Python | pandas_datareaders_unofficial/__init__.py | movermeyer/pandas_datareaders_unofficial | 458dcf473d070cd7686d53d4a9b479cbe0ab9218 | [
"BSD-3-Clause"
] | 18 | 2015-02-05T01:42:51.000Z | 2020-12-27T19:24:25.000Z | pandas_datareaders_unofficial/__init__.py | movermeyer/pandas_datareaders_unofficial | 458dcf473d070cd7686d53d4a9b479cbe0ab9218 | [
"BSD-3-Clause"
] | 1 | 2015-01-12T11:08:02.000Z | 2015-01-13T09:14:47.000Z | pandas_datareaders_unofficial/__init__.py | femtotrader/pandas_datareaders | 458dcf473d070cd7686d53d4a9b479cbe0ab9218 | [
"BSD-3-Clause"
] | 13 | 2015-09-10T19:39:51.000Z | 2022-01-06T17:08:35.000Z | from .module import DataReader
| 15.5 | 30 | 0.83871 | 4 | 31 | 6.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.129032 | 31 | 1 | 31 | 31 | 0.962963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
9b7d5afdb94d1a03ffbdf2fd4aee7458048629b9 | 142 | py | Python | python/illusionist/utils.py | ocefpaf/illusionist | fc4db24230a5ed6f5756df3aacef344fe12fabf3 | [
"Apache-2.0"
] | 9 | 2020-06-11T17:09:17.000Z | 2021-11-16T13:44:05.000Z | python/illusionist/utils.py | ocefpaf/illusionist | fc4db24230a5ed6f5756df3aacef344fe12fabf3 | [
"Apache-2.0"
] | 2 | 2020-08-30T19:58:30.000Z | 2021-09-29T02:08:55.000Z | python/illusionist/utils.py | ocefpaf/illusionist | fc4db24230a5ed6f5756df3aacef344fe12fabf3 | [
"Apache-2.0"
] | 1 | 2021-09-30T17:20:32.000Z | 2021-09-30T17:20:32.000Z | import inspect
def get_source(code):
"""
Return the source code for a module or function
"""
return inspect.getsource(code)
| 15.777778 | 51 | 0.669014 | 19 | 142 | 4.947368 | 0.736842 | 0.212766 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.246479 | 142 | 8 | 52 | 17.75 | 0.878505 | 0.330986 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
9b9c1ed6fa1ee853bff99d7125bb0a457cf8f15d | 983 | py | Python | algopy/fft/fft.py | arthus701/algopy | 1e2430f803289bbaed6bbdff6c28f98d7767835c | [
"Unlicense"
] | 54 | 2015-03-05T13:38:08.000Z | 2021-11-29T11:54:48.000Z | algopy/fft/fft.py | arthus701/algopy | 1e2430f803289bbaed6bbdff6c28f98d7767835c | [
"Unlicense"
] | 7 | 2016-04-06T11:25:00.000Z | 2020-11-09T13:53:20.000Z | algopy/fft/fft.py | arthus701/algopy | 1e2430f803289bbaed6bbdff6c28f98d7767835c | [
"Unlicense"
] | 13 | 2015-01-17T17:05:56.000Z | 2021-08-05T01:13:16.000Z | import string
import numpy
import numpy.linalg
import scipy.linalg
from algopy import UTPM, Function
def fft(a, n=None, axis=-1):
"""
equivalent to numpy.fft.fft(a, n=None, axis=-1)
"""
if isinstance(a, UTPM):
return UTPM.fft(a, n=n, axis=axis)
elif isinstance(a, Function):
return Function.fft(a, n=n, axis=axis)
elif isinstance(a, numpy.ndarray):
return numpy.fft.fft(a, n=n, axis=axis)
else:
raise NotImplementedError('don\'t know what to do with this instance')
def ifft(a, n=None, axis=-1):
"""
equivalent to numpy.fft.ifft(a, n=None, axis=-1)
"""
if isinstance(a, UTPM):
return UTPM.ifft(a, n=n, axis=axis)
elif isinstance(a, Function):
return Function.ifft(a, n=n, axis=axis)
elif isinstance(a, numpy.ndarray):
return numpy.fft.ifft(a, n=n, axis=axis)
else:
raise NotImplementedError('don\'t know what to do with this instance')
| 20.914894 | 78 | 0.61648 | 149 | 983 | 4.067114 | 0.234899 | 0.033003 | 0.029703 | 0.069307 | 0.849835 | 0.849835 | 0.815182 | 0.815182 | 0.815182 | 0.689769 | 0 | 0.005413 | 0.24822 | 983 | 46 | 79 | 21.369565 | 0.814614 | 0.099695 | 0 | 0.434783 | 0 | 0 | 0.009501 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.086957 | false | 0 | 0.217391 | 0 | 0.565217 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
32d110b3404a920bff8d2ae094508eeb7f47ef45 | 201 | py | Python | pandas/io/json/__init__.py | vimalromeo/pandas | 7c14e4f14aff216be558bf5d4d2d00b4838c2360 | [
"PSF-2.0",
"Apache-2.0",
"BSD-3-Clause-No-Nuclear-License-2014",
"MIT",
"ECL-2.0",
"BSD-3-Clause"
] | 6,989 | 2017-07-18T06:23:18.000Z | 2022-03-31T15:58:36.000Z | venv/lib/python3.7/site-packages/pandas/io/json/__init__.py | John1001Song/Big-Data-Robo-Adviser | 9444dce96954c546333d5aecc92a06c3bfd19aa5 | [
"MIT"
] | 1,978 | 2017-07-18T09:17:58.000Z | 2022-03-31T14:28:43.000Z | venv/lib/python3.7/site-packages/pandas/io/json/__init__.py | John1001Song/Big-Data-Robo-Adviser | 9444dce96954c546333d5aecc92a06c3bfd19aa5 | [
"MIT"
] | 1,228 | 2017-07-18T09:03:13.000Z | 2022-03-29T05:57:40.000Z | from .json import to_json, read_json, loads, dumps # noqa
from .normalize import json_normalize # noqa
from .table_schema import build_table_schema # noqa
del json, normalize, table_schema # noqa
| 33.5 | 58 | 0.781095 | 30 | 201 | 5 | 0.433333 | 0.22 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.159204 | 201 | 5 | 59 | 40.2 | 0.887574 | 0.094527 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.75 | 0 | 0.75 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
32e5510f024ecf93e131c4faaaa3be6ac3aaf937 | 202 | py | Python | kirppu_project/test/test_doctests.py | Glowieh/kirppu | 95f3e98c594ca7f02ed4ec311da3e558d76ea5b3 | [
"MIT"
] | null | null | null | kirppu_project/test/test_doctests.py | Glowieh/kirppu | 95f3e98c594ca7f02ed4ec311da3e558d76ea5b3 | [
"MIT"
] | null | null | null | kirppu_project/test/test_doctests.py | Glowieh/kirppu | 95f3e98c594ca7f02ed4ec311da3e558d76ea5b3 | [
"MIT"
] | null | null | null | import doctest
from kirppu import util, models
def load_tests(loader, tests, ignore):
tests.addTests(doctest.DocTestSuite(util))
tests.addTests(doctest.DocTestSuite(models))
return tests
| 20.2 | 48 | 0.762376 | 25 | 202 | 6.12 | 0.56 | 0.169935 | 0.261438 | 0.418301 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148515 | 202 | 9 | 49 | 22.444444 | 0.889535 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
fd3aa799c6d64745f6c9ba6713857b876d9ada36 | 43 | py | Python | pycroaktools/shapes/__init__.py | 20centcroak/PyCroakTools | 7bef42ad394636a65a4011cf63e22c40f412df8e | [
"MIT"
] | null | null | null | pycroaktools/shapes/__init__.py | 20centcroak/PyCroakTools | 7bef42ad394636a65a4011cf63e22c40f412df8e | [
"MIT"
] | null | null | null | pycroaktools/shapes/__init__.py | 20centcroak/PyCroakTools | 7bef42ad394636a65a4011cf63e22c40f412df8e | [
"MIT"
] | null | null | null | from pycroaktools.shapes.shape import Shape | 43 | 43 | 0.883721 | 6 | 43 | 6.333333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.069767 | 43 | 1 | 43 | 43 | 0.95 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
fd65438a8775fda19321cc0703c605934afa08ec | 17,492 | py | Python | pybind/slxos/v17r_2_00/cpu_state/all_partition/cpu_allpart_util/__init__.py | extremenetworks/pybind | 44c467e71b2b425be63867aba6e6fa28b2cfe7fb | [
"Apache-2.0"
] | null | null | null | pybind/slxos/v17r_2_00/cpu_state/all_partition/cpu_allpart_util/__init__.py | extremenetworks/pybind | 44c467e71b2b425be63867aba6e6fa28b2cfe7fb | [
"Apache-2.0"
] | null | null | null | pybind/slxos/v17r_2_00/cpu_state/all_partition/cpu_allpart_util/__init__.py | extremenetworks/pybind | 44c467e71b2b425be63867aba6e6fa28b2cfe7fb | [
"Apache-2.0"
] | 1 | 2021-11-05T22:15:42.000Z | 2021-11-05T22:15:42.000Z |
from operator import attrgetter
import pyangbind.lib.xpathhelper as xpathhelper
from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType
from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType
from pyangbind.lib.base import PybindBase
from decimal import Decimal
from bitarray import bitarray
import __builtin__
class cpu_allpart_util(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module brocade-RAS-operational - based on the path /cpu-state/all-partition/cpu-allpart-util. Each member element of
the container is represented as a class variable - with a specific
YANG type.
YANG Description: CPU utilization percentage of the blade MM/LC
"""
__slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__cpu_blade_name','__cpu_util_current','__cpu_util_user','__cpu_util_kernel','__cpu_util_iowait',)
_yang_name = 'cpu-allpart-util'
_rest_name = 'cpu-allpart-util'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
path_helper_ = kwargs.pop("path_helper", None)
if path_helper_ is False:
self._path_helper = False
elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper):
self._path_helper = path_helper_
elif hasattr(self, "_parent"):
path_helper_ = getattr(self._parent, "_path_helper", False)
self._path_helper = path_helper_
else:
self._path_helper = False
extmethods = kwargs.pop("extmethods", None)
if extmethods is False:
self._extmethods = False
elif extmethods is not None and isinstance(extmethods, dict):
self._extmethods = extmethods
elif hasattr(self, "_parent"):
extmethods = getattr(self._parent, "_extmethods", None)
self._extmethods = extmethods
else:
self._extmethods = False
self.__cpu_util_user = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-user", rest_name="cpu-util-user", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
self.__cpu_util_iowait = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-iowait", rest_name="cpu-util-iowait", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
self.__cpu_blade_name = YANGDynClass(base=unicode, is_leaf=True, yang_name="cpu-blade-name", rest_name="cpu-blade-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='string', is_config=False)
self.__cpu_util_kernel = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-kernel", rest_name="cpu-util-kernel", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
self.__cpu_util_current = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-current", rest_name="cpu-util-current", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return [u'cpu-state', u'all-partition', u'cpu-allpart-util']
def _rest_path(self):
if hasattr(self, "_parent"):
if self._rest_name:
return self._parent._rest_path()+[self._rest_name]
else:
return self._parent._rest_path()
else:
return [u'cpu-state', u'all-partition', u'cpu-allpart-util']
def _get_cpu_blade_name(self):
"""
Getter method for cpu_blade_name, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_blade_name (string)
YANG Description: MM/LC name
"""
return self.__cpu_blade_name
def _set_cpu_blade_name(self, v, load=False):
"""
Setter method for cpu_blade_name, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_blade_name (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_cpu_blade_name is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_cpu_blade_name() directly.
YANG Description: MM/LC name
"""
parent = getattr(self, "_parent", None)
if parent is not None and load is False:
raise AttributeError("Cannot set keys directly when" +
" within an instantiated list")
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="cpu-blade-name", rest_name="cpu-blade-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='string', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """cpu_blade_name must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="cpu-blade-name", rest_name="cpu-blade-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='string', is_config=False)""",
})
self.__cpu_blade_name = t
if hasattr(self, '_set'):
self._set()
def _unset_cpu_blade_name(self):
self.__cpu_blade_name = YANGDynClass(base=unicode, is_leaf=True, yang_name="cpu-blade-name", rest_name="cpu-blade-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='string', is_config=False)
def _get_cpu_util_current(self):
"""
Getter method for cpu_util_current, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_current (decimal64)
YANG Description: Current Total CPU utilization
"""
return self.__cpu_util_current
def _set_cpu_util_current(self, v, load=False):
"""
Setter method for cpu_util_current, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_current (decimal64)
If this variable is read-only (config: false) in the
source YANG file, then _set_cpu_util_current is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_cpu_util_current() directly.
YANG Description: Current Total CPU utilization
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-current", rest_name="cpu-util-current", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """cpu_util_current must be of a type compatible with decimal64""",
'defined-type': "decimal64",
'generated-type': """YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-current", rest_name="cpu-util-current", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)""",
})
self.__cpu_util_current = t
if hasattr(self, '_set'):
self._set()
def _unset_cpu_util_current(self):
self.__cpu_util_current = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-current", rest_name="cpu-util-current", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
def _get_cpu_util_user(self):
"""
Getter method for cpu_util_user, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_user (decimal64)
YANG Description: Current CPU utilization by user process
"""
return self.__cpu_util_user
def _set_cpu_util_user(self, v, load=False):
"""
Setter method for cpu_util_user, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_user (decimal64)
If this variable is read-only (config: false) in the
source YANG file, then _set_cpu_util_user is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_cpu_util_user() directly.
YANG Description: Current CPU utilization by user process
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-user", rest_name="cpu-util-user", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """cpu_util_user must be of a type compatible with decimal64""",
'defined-type': "decimal64",
'generated-type': """YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-user", rest_name="cpu-util-user", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)""",
})
self.__cpu_util_user = t
if hasattr(self, '_set'):
self._set()
def _unset_cpu_util_user(self):
self.__cpu_util_user = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-user", rest_name="cpu-util-user", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
def _get_cpu_util_kernel(self):
"""
Getter method for cpu_util_kernel, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_kernel (decimal64)
YANG Description: Current CPU utilization by kernel processes
"""
return self.__cpu_util_kernel
def _set_cpu_util_kernel(self, v, load=False):
"""
Setter method for cpu_util_kernel, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_kernel (decimal64)
If this variable is read-only (config: false) in the
source YANG file, then _set_cpu_util_kernel is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_cpu_util_kernel() directly.
YANG Description: Current CPU utilization by kernel processes
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-kernel", rest_name="cpu-util-kernel", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """cpu_util_kernel must be of a type compatible with decimal64""",
'defined-type': "decimal64",
'generated-type': """YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-kernel", rest_name="cpu-util-kernel", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)""",
})
self.__cpu_util_kernel = t
if hasattr(self, '_set'):
self._set()
def _unset_cpu_util_kernel(self):
self.__cpu_util_kernel = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-kernel", rest_name="cpu-util-kernel", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
def _get_cpu_util_iowait(self):
"""
Getter method for cpu_util_iowait, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_iowait (decimal64)
YANG Description: Current CPU utilization in iowait
"""
return self.__cpu_util_iowait
def _set_cpu_util_iowait(self, v, load=False):
"""
Setter method for cpu_util_iowait, mapped from YANG variable /cpu_state/all_partition/cpu_allpart_util/cpu_util_iowait (decimal64)
If this variable is read-only (config: false) in the
source YANG file, then _set_cpu_util_iowait is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_cpu_util_iowait() directly.
YANG Description: Current CPU utilization in iowait
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-iowait", rest_name="cpu-util-iowait", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """cpu_util_iowait must be of a type compatible with decimal64""",
'defined-type': "decimal64",
'generated-type': """YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-iowait", rest_name="cpu-util-iowait", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)""",
})
self.__cpu_util_iowait = t
if hasattr(self, '_set'):
self._set()
def _unset_cpu_util_iowait(self):
self.__cpu_util_iowait = YANGDynClass(base=RestrictedPrecisionDecimalType(precision=2), is_leaf=True, yang_name="cpu-util-iowait", rest_name="cpu-util-iowait", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-RAS-operational', defining_module='brocade-RAS-operational', yang_type='decimal64', is_config=False)
cpu_blade_name = __builtin__.property(_get_cpu_blade_name)
cpu_util_current = __builtin__.property(_get_cpu_util_current)
cpu_util_user = __builtin__.property(_get_cpu_util_user)
cpu_util_kernel = __builtin__.property(_get_cpu_util_kernel)
cpu_util_iowait = __builtin__.property(_get_cpu_util_iowait)
_pyangbind_elements = {'cpu_blade_name': cpu_blade_name, 'cpu_util_current': cpu_util_current, 'cpu_util_user': cpu_util_user, 'cpu_util_kernel': cpu_util_kernel, 'cpu_util_iowait': cpu_util_iowait, }
| 60.317241 | 406 | 0.7496 | 2,386 | 17,492 | 5.201593 | 0.076697 | 0.060914 | 0.049633 | 0.045685 | 0.827331 | 0.795907 | 0.766578 | 0.751027 | 0.721779 | 0.715333 | 0 | 0.005698 | 0.137206 | 17,492 | 289 | 407 | 60.525952 | 0.816658 | 0.191173 | 0 | 0.44186 | 0 | 0.02907 | 0.32768 | 0.175244 | 0 | 0 | 0 | 0 | 0 | 1 | 0.104651 | false | 0 | 0.046512 | 0 | 0.273256 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
b5dc76ec5329df41516a006dcd2c897b0b60a3e9 | 9,324 | py | Python | tests/test_main.py | WIPACrepo/publication-web-db | f5d77f43c89377449f4fbe952f6b1dcfc458c91a | [
"MIT"
] | null | null | null | tests/test_main.py | WIPACrepo/publication-web-db | f5d77f43c89377449f4fbe952f6b1dcfc458c91a | [
"MIT"
] | 16 | 2020-09-26T00:49:56.000Z | 2021-09-09T19:03:42.000Z | tests/test_main.py | WIPACrepo/publication-web-db | f5d77f43c89377449f4fbe952f6b1dcfc458c91a | [
"MIT"
] | null | null | null | import asyncio
import pytest
from rest_tools.client import AsyncSession
from bs4 import BeautifulSoup
from pubs.utils import nowstr, add_pub
from .util import port, mongo_client, server
async def get_pubs(*args, **kwargs):
s = AsyncSession(retries=0)
r = await asyncio.wrap_future(s.get(*args, **kwargs))
r.raise_for_status()
soup = BeautifulSoup(r.content, 'html.parser')
return soup.select('.publication')
@pytest.mark.asyncio
async def test_no_pubs(server):
db, url = server
pubs = await get_pubs(url)
assert pubs == []
@pytest.mark.asyncio
async def test_single_pub(server):
db, url = server
await add_pub(db, title='Test Title', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
pubs = await get_pubs(url)
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title'
assert pubs[0].select('.author')[0].string == 'auth'
assert pubs[0].select('.project')[0].string == 'IceCube'
@pytest.mark.asyncio
async def test_multiple_pubs(server):
db, url = server
await add_pub(db, title='Test Title', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title3', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
pubs = await get_pubs(url)
assert len(pubs) == 3
# order by reversed date
assert pubs[0].select('.title')[0].string == 'Test Title3'
assert pubs[1].select('.title')[0].string == 'Test Title2'
assert pubs[2].select('.title')[0].string == 'Test Title'
@pytest.mark.asyncio
async def test_project(server):
db, url = server
await add_pub(db, title='Test Title', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['hawc'])
pubs = await get_pubs(url, params={'projects': 'hawc'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
assert pubs[0].select('.project')[0].string == 'HAWC'
@pytest.mark.asyncio
async def test_multi_project(server):
db, url = server
await add_pub(db, title='Test Title', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['hawc'])
await add_pub(db, title='Test Title3', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube','hawc'])
pubs = await get_pubs(url, params={'projects': ['hawc', 'icecube']})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title3'
assert set(x.string for x in pubs[0].select('.project')) == set(['HAWC', 'IceCube'])
@pytest.mark.asyncio
async def test_hide_projects(server):
db, url = server
await add_pub(db, title='Test Title', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['hawc'])
pubs = await get_pubs(url, params={'projects': 'hawc', 'hide_projects': True})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
assert pubs[0].select('.project') == []
pubs = await get_pubs(url, params={'projects': 'hawc', 'hide_projects': 'false'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
assert pubs[0].select('.project') != []
@pytest.mark.asyncio
async def test_dates(server):
db, url = server
await add_pub(db, title='Test Title1', authors=['auth'],
pub_type="journal", citation="TestJournal", date='2020-01-02',
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="journal", citation="TestJournal", date='2020-02-03',
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title3', authors=['auth'],
pub_type="journal", citation="TestJournal", date='2020-03-04',
downloads=[], projects=['icecube'])
pubs = await get_pubs(url, params={'start_date': '2020-02-02'})
assert len(pubs) == 2
# order by reversed date
assert pubs[0].select('.title')[0].string == 'Test Title3'
assert pubs[1].select('.title')[0].string == 'Test Title2'
pubs = await get_pubs(url, params={'end_date': '2020-02-02'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title1'
pubs = await get_pubs(url, params={'start_date': '2020-02-01', 'end_date': '2020-03-01'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
pubs = await get_pubs(url, params={'start_date': '2020-04-01'})
assert len(pubs) == 0
pubs = await get_pubs(url, params={'end_date': '2019-04-01'})
assert len(pubs) == 0
@pytest.mark.asyncio
async def test_types(server):
db, url = server
await add_pub(db, title='Test Title1', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="proceeding", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title3', authors=['auth'],
pub_type="thesis", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
pubs = await get_pubs(url, params={'type': 'journal'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title1'
pubs = await get_pubs(url, params={'type': 'proceeding'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
pubs = await get_pubs(url, params={'type': 'thesis'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title3'
pubs = await get_pubs(url, params={'type': ['journal','thesis']})
assert len(pubs) == 2
assert pubs[0].select('.title')[0].string == 'Test Title3'
assert pubs[1].select('.title')[0].string == 'Test Title1'
@pytest.mark.asyncio
async def test_title(server):
db, url = server
await add_pub(db, title='Test Title1', authors=['auth'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth'],
pub_type="proceeding", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title3', authors=['auth'],
pub_type="thesis", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
pubs = await get_pubs(url, params={'search': 'title1'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title1'
@pytest.mark.asyncio
async def test_authors(server):
db, url = server
await add_pub(db, title='Test Title1', authors=['auth1'],
pub_type="journal", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title2', authors=['auth2'],
pub_type="proceeding", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
await add_pub(db, title='Test Title3', authors=['auth1', 'auth3'],
pub_type="thesis", citation="TestJournal", date=nowstr(),
downloads=[], projects=['icecube'])
pubs = await get_pubs(url, params={'authors': 'auth1'})
assert len(pubs) == 2
assert pubs[0].select('.title')[0].string == 'Test Title3'
assert pubs[1].select('.title')[0].string == 'Test Title1'
pubs = await get_pubs(url, params={'authors': 'auth2'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title2'
pubs = await get_pubs(url, params={'authors': 'auth3'})
assert len(pubs) == 1
assert pubs[0].select('.title')[0].string == 'Test Title3'
pubs = await get_pubs(url, params={'authors': 'auth4'})
assert len(pubs) == 0
| 38.37037 | 93 | 0.600064 | 1,144 | 9,324 | 4.805944 | 0.086538 | 0.050928 | 0.046017 | 0.054383 | 0.891779 | 0.887232 | 0.838669 | 0.80793 | 0.795016 | 0.778647 | 0 | 0.026634 | 0.21879 | 9,324 | 242 | 94 | 38.528926 | 0.728171 | 0.004826 | 0 | 0.685083 | 0 | 0 | 0.186934 | 0 | 0 | 0 | 0 | 0 | 0.270718 | 1 | 0 | false | 0 | 0.033149 | 0 | 0.038674 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
bd4904f3bd644736f99a726d29ede081e7185019 | 120 | py | Python | input_string_to_list.py | esltech/python_class | d75483005848b9b6aed86f124efc0cd254322bc5 | [
"MIT"
] | null | null | null | input_string_to_list.py | esltech/python_class | d75483005848b9b6aed86f124efc0cd254322bc5 | [
"MIT"
] | null | null | null | input_string_to_list.py | esltech/python_class | d75483005848b9b6aed86f124efc0cd254322bc5 | [
"MIT"
] | null | null | null | inp=input("Please enter a string:")
print("Converting to a list:",list(inp))
print("Converting to a tuple:",tuple(inp)) | 30 | 42 | 0.716667 | 20 | 120 | 4.3 | 0.55 | 0.348837 | 0.395349 | 0.418605 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 120 | 4 | 42 | 30 | 0.796296 | 0 | 0 | 0 | 0 | 0 | 0.53719 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.666667 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
1fe37ea5879d3ee303383857c01ed3818e4d582a | 26 | py | Python | cana/thermal/__init__.py | cana-asteroids/cana | afb7b0155cda8578c487d43a1a665f8823486633 | [
"MIT"
] | 6 | 2019-11-24T16:30:40.000Z | 2021-08-23T19:29:43.000Z | cana/thermal/__init__.py | cana-asteroids/cana | afb7b0155cda8578c487d43a1a665f8823486633 | [
"MIT"
] | 1 | 2020-06-18T17:23:24.000Z | 2021-09-08T16:51:50.000Z | cana/thermal/__init__.py | depra/cana | 95a3af2f72195befcb6bf7a65eb4fecbfdf52f5b | [
"MIT"
] | null | null | null | from .models import NEATM
| 13 | 25 | 0.807692 | 4 | 26 | 5.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.153846 | 26 | 1 | 26 | 26 | 0.954545 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
9501b8eebcd5346ae69a7015fc096dbf0179926d | 20 | py | Python | copypastor/src/__init__.py | Venomen/copypastor | add35e6b4ea17632c2b678a629d541b74b55ff0e | [
"MIT"
] | null | null | null | copypastor/src/__init__.py | Venomen/copypastor | add35e6b4ea17632c2b678a629d541b74b55ff0e | [
"MIT"
] | null | null | null | copypastor/src/__init__.py | Venomen/copypastor | add35e6b4ea17632c2b678a629d541b74b55ff0e | [
"MIT"
] | null | null | null | from ..src import *
| 10 | 19 | 0.65 | 3 | 20 | 4.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 20 | 1 | 20 | 20 | 0.8125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
951aa30369427169a8c0ac19a420215235b87995 | 32 | py | Python | aos_sw_api/mac_table/__init__.py | KennethSoelberg/AOS-Switch | a5a2c54917bbb69fab044bf0b313bcf795642d30 | [
"MIT"
] | null | null | null | aos_sw_api/mac_table/__init__.py | KennethSoelberg/AOS-Switch | a5a2c54917bbb69fab044bf0b313bcf795642d30 | [
"MIT"
] | 1 | 2020-12-24T15:36:56.000Z | 2021-01-28T23:19:57.000Z | aos_sw_api/mac_table/__init__.py | KennethSoelberg/AOS-Switch | a5a2c54917bbb69fab044bf0b313bcf795642d30 | [
"MIT"
] | 1 | 2021-02-16T23:26:28.000Z | 2021-02-16T23:26:28.000Z | from ._mac_table import MacTable | 32 | 32 | 0.875 | 5 | 32 | 5.2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.09375 | 32 | 1 | 32 | 32 | 0.896552 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
1f12718fca2ed6668acb76840c9652c627ee675c | 30 | py | Python | src/__init__.py | dhimmel/hetmech | 4c7dc77054a02d7da4c30c2a9b0eca391cf5b6b5 | [
"BSD-3-Clause"
] | 10 | 2017-08-20T17:12:57.000Z | 2019-03-26T21:42:28.000Z | src/__init__.py | greenelab/hetmech | ca460f70a247ef456c930c7e64df24f59dc2b338 | [
"BSD-3-Clause"
] | 121 | 2017-03-16T19:20:31.000Z | 2021-01-21T16:15:55.000Z | src/__init__.py | dhimmel/hetmech | 4c7dc77054a02d7da4c30c2a9b0eca391cf5b6b5 | [
"BSD-3-Clause"
] | 7 | 2017-03-27T23:02:11.000Z | 2019-03-27T15:47:52.000Z | from .utils import get_config
| 15 | 29 | 0.833333 | 5 | 30 | 4.8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 30 | 1 | 30 | 30 | 0.923077 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
1f214606cbdbe99f441e16c2f79d050ac7ff0a67 | 183 | py | Python | PyWeiboSpy/exceptions.py | veikai/PyWeiboSpy | cf9aebeba9102052f2ecbdbed3662d1c71933775 | [
"Apache-2.0"
] | 1 | 2020-10-24T15:38:03.000Z | 2020-10-24T15:38:03.000Z | PyWeiboSpy/exceptions.py | veikai/PyWeiboSpy | cf9aebeba9102052f2ecbdbed3662d1c71933775 | [
"Apache-2.0"
] | null | null | null | PyWeiboSpy/exceptions.py | veikai/PyWeiboSpy | cf9aebeba9102052f2ecbdbed3662d1c71933775 | [
"Apache-2.0"
] | null | null | null | class SpyError(Exception):
def __init__(self, error):
super().__init__(error)
class LoginError(SpyError):
def __init__(self, error):
super().__init__(error)
| 20.333333 | 31 | 0.661202 | 20 | 183 | 5.25 | 0.45 | 0.133333 | 0.209524 | 0.304762 | 0.571429 | 0.571429 | 0.571429 | 0 | 0 | 0 | 0 | 0 | 0.20765 | 183 | 8 | 32 | 22.875 | 0.724138 | 0 | 0 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 6 |
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